4.9 on Clutch
Data engineering services
Use Syndicode’s data engineering services to build reliable data pipelines, modern data infrastructure, and real-time analytics that turn fragmented data into decisions while strengthening data integrity across your organization. We help you reduce time to insight, cut infrastructure costs, and scale with confidence.
Data engineering services we provide
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Data strategy and architecture
We start with your business goals, not just your tools. Our team will audit your company’s data sources, workflows, and current data infrastructure, then design a scalable architecture that supports clean data ingestion, efficient data processing, and strong data governance frameworks. This ensures every downstream initiative, from BI to AI, is built on a stable foundation.
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ETL/ELT and data pipeline development
Syndicode designs and implements robust ETL/ELT workflows that move data from SaaS tools, transactional systems, third-party APIs, and files into your central platform. We build pipelines that simplify data ingestion, streamline data processing, and prevent data silos as your systems grow. Our engineers deliver observable, testable workflows that maintain high data integrity at scale.
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Data warehouse and lakehouse development
Using platforms like Snowflake, BigQuery, Redshift, Azure Synapse, and Databricks, our engineers design schemas, partitioning, and storage layers optimized for analytics and cost. With properly modeled data, your BI, product analytics, and ML teams will gain fast, reliable access to a single source of truth.
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Real-time and streaming data platforms
For businesses that can’t wait for next-day reports, we implement streaming architectures based on Apache Kafka, Kinesis, or Pub/Sub. Our data engineers create real-time pipelines, event hubs, and materialized views to power live dashboards, personalization engines, fraud detection, and operational alerts. This will let you react to customer behavior and system events in seconds, not hours.
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Analytics, BI enablement, and data products
Our data engineering services will help you turn raw data into practical decision tools. Syndicode prepares analytics-ready datasets, semantic layers, and governed metrics definitions for tools like Power BI, Looker, and Tableau. These models also create a foundation for advanced analytics and data science services to support deeper insights and predictive capabilities across your organization.
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Data platform modernization and cloud migration
If you’re limited by legacy on-prem SQL servers or fragile data pipelines, we’ll refactor outdated systems and replace legacy ingestion scripts with modern data processing workflows. Your upgraded platform will align with modern data governance frameworks and scale along with your wider enterprise software development and software development outsourcing strategy.
Challenges we solve
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Data quality issues
Seeing duplicate records, blank fields in reports, or teams using completely different data sources? These are clear signs of data quality issues. Syndicode helps by bringing all your data into one place, cleaning and standardizing it, and adding automated checks with full lineage tracking. The result is reliable, consistent information your teams can trust and use with confidence.
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Slow reporting
If your dashboards take minutes to load or reports only update after someone manually fixes them, this may point to slow, outdated reporting workflows. Syndicode’s data engineering services will automate raw data processing, optimize ingestion patterns, and remove hidden data silos, giving your team consistently fast insights backed by strong data engineering expertise.
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Computing costs increase
Cloud bills rising fast, storage filled with unused tables, or pipelines rerunning for no clear reason are common signs of inefficient data architecture. Syndicode will optimize storage, streamline data processing pipelines, and remove redundant ingestion paths that inflate cloud spending. Our approach ensures efficient operations while preserving data integrity and platform performance.
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Integration blockers
Issues when integrating new tools often stem from legacy systems using outdated schemas or identifiers. Syndicode applies clean schema design and modern data integration engineering services to unify identifiers, eliminate data silos, and streamline ingestion and data processing for seamless integrations.
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Growing tech debt
Syndicode’s engineers fix old scripts no one understands, data pipelines held together by patches, or tables no one can safely delete. We restructure workflows, document logic, and replace fragile scripts with maintainable pipelines. Your platform will become stable, predictable, and far easier for new engineers to work with.
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Metrics that change meaning
Sudden spikes or drops in KPIs, or teams debating what a metric really means, often signal drifting transformations or missing semantic layers. Syndicode standardizes metric definitions, aligns transformations, and implements governed semantic layers built on reliable data processing, ensuring consistent KPIs and ensuring every team measures success the same way.
Struggling with fragmented data?
Syndicode can help you centralize data, fix data quality issues, and build a platform your teams actually trust. Together, we’ll align architecture, tools, and processes around your business goals, so every report and feature is powered by reliable data.
Talk to our teamWhy choose data engineering services from Syndicode?
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Modern data stack aligned with your roadmap
We’ll design your data platform around your long-term product and analytics strategy, not isolated tools. Our architects will ensure each component, from ingestion to BI, works together and can evolve. This alignment reduces future rework, keeps maintenance predictable, and supports expansion into new markets and features.
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Faster time to insight and experimentation
Syndicode focuses on reducing the time from a business question to a validated answer. Standardized datasets, semantic layers, and reliable data pipelines mean analysts and product teams spend more time exploring ideas, not fixing data. You’ll experiment faster, validate features sooner, and make data-driven decisions with greater confidence.
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Better data quality, governance, and compliance
Our engineers embed data quality checks, lineage, and access controls directly into pipelines and models, ensuring compliance with regulations such as GDPR. These practices strengthen trust and create a strong foundation for AI development, enabling your organization to scale into more advanced use cases confidently.
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Optimized cloud and infrastructure costs
A high-quality data platform should be both powerful and cost-efficient. We optimize storage formats, partitioning, scheduling, and compute configurations to avoid waste. By right-sizing clusters, consolidating tools, and eliminating redundant jobs, Syndicode will help you keep cloud bills under control while preserving performance and reliability.
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Transparent collaboration and end-to-end delivery
From discovery workshops to handover, we work as an extension of your team. Business stakeholders, engineers, and analysts are part of the same conversation, supported by clear documentation and demos. Combining software development consulting with hands-on data engineering, we reduce misalignment, cut delivery risks, and keep your internal team fully in the loop.
Our data engineering services delivery process
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Discovery
We begin our data engineering services delivery by mapping your business objectives to specific data use cases: reporting, personalization, forecasting, or product analytics. Our architects assess your current data infrastructure, identify broken data ingestion paths, and highlight inefficiencies in data processing that cause quality issues or data silos.
This step identifies critical data sources, pain points, and quick wins, helping you establish a clear baseline of where you are before implementation begins, and extract more value from raw datasets should you use our data mining services. -
Architecture and roadmap design
Based on the assessment, we design an architecture covering ingestion, storage, data processing, and data governance, ensuring the entire platform supports consistent growth and long-term data integrity. Our data architects and senior engineers will choose patterns and technologies that fit your budget, skills, and regulatory environment. We define phases, milestones, and success metrics, ensuring alignment with your wider turnkey software development and product plans. This gives you a realistic, phased roadmap rather than a risky “big bang” transformation.
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Platform setup and pipeline implementation
Our data engineering specialists provision cloud resources, configure CI/CD, and implement core ETL/ELT pipelines using Airflow, dbt, or cloud-native orchestrators, all supported by our DevOps expertise to ensure resilient, scalable, and observable data infrastructure.
We apply best practices for versioning, testing, and observability so your data assets behave like high-quality software. Business value appears early through initial dashboards and datasets, while the platform remains flexible enough to support additional domains and features. -
Analytics enablement and integration
Once foundational pipelines are stable, we focus on consumption. Engineers, analysts, and product stakeholders co-create analytics-ready models, semantic layers, and KPIs that power BI tools, internal admin panels, and external user-facing features. We integrate with your existing website development or product interfaces where needed. This step turns the platform into daily decision support, empowering teams across departments to use trustworthy, consistent data.
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Optimization, training, and ongoing evolution
After launch, we monitor performance, costs, and user adoption. Our data engineering team fine-tunes pipelines, adjusts resource usage, and refactors models as business questions evolve. We run knowledge transfer sessions so your in-house engineers and analysts can extend the stack confidently. Once your team is equipped to take ownership, you can continue to rely on Syndicode as a long-term partner for new domains and initiatives or for periodic health checks, depending on your preferred engagement model.
Need a roadmap for your data platform?
If you’re unsure where to start, we’ll run a focused assessment to map your current stack, identify gaps, and define a phased, realistic plan. You’ll see where to invest first and how data engineering supports your wider product strategy.
Book a data auditOur data engineering tech stack
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Cloud platforms
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Data warehouses & lakehouses
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Data lakes & storage
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Orchestration
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ETL/ELT & integration
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Streaming & real-time
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Data governance & quality
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Analytics & BI
Industries we support with data engineering
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Marketplaces
Optimize conversion, inventory, and marketing ROI with unified customer, product, and transaction data for your retail or marketplace platform.
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Fintech
Enable real-time risk scoring, compliance reporting, and customer analytics on secure, governed data platforms.
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Healthcare
Gather clinical, operational, and device data while respecting privacy and regulatory requirements.
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Logistics
Gain visibility into shipments, routes, and capacity for improved planning and on-time delivery.
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E-learning
Use learner behavior and content performance data to improve course design and engagement.
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SaaS/B2B
Build product analytics, health scores, and usage-based billing on a modern data stack.
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Media
Unify campaign, audience, and attribution data to drive more effective spend decisions.
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Travel
Combine booking, pricing, and behavioral data to improve personalization and yield management.
Engagement models
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End-to-end data platform delivery
Choose this model if you want Syndicode to handle the entire lifecycle from discovery to support. We provide a cross-functional team of data engineering experts, architects, QA, DevOps, and product roles. You keep a single point of accountability, predictable costs, and a clear roadmap. This works especially well if data engineering is a new capability in your organization.
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Dedicated data engineering team
If you already have a data strategy and backlog, Syndicode can assemble a dedicated team focused on your data platform. The team operates as a long-term extension of your data engineering organization with shared rituals and tools. You retain control over priorities while gaining extra capacity, specialized skills, and consistent velocity without the overhead of hiring in-house.
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Team extension
For organizations with an established stack but limited bandwidth, we add individual data engineering specialists, analytics engineers, or architects to your existing team. They’ll follow your processes, tools, and culture, while bringing Syndicode’s proven practices from custom software development and enterprise projects. This model helps you clear bottlenecks, accelerate critical initiatives, and cover skill gaps quickly.
Frequently asked questions
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How do I know if my company is ready for data engineering services?
You’re ready when important decisions rely on manual spreadsheets, conflicting reports, or slow IT requests. If teams debate whose numbers are “right,” or if launching a new dashboard takes weeks, a structured approach is needed. A data engineering services company like Syndicode can assess your tools, skills, and priorities and outline a pragmatic roadmap that matches your maturity and budget.
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Which technologies and cloud platforms do you work with?
Our data engineering teams work with major cloud providers, such as AWS, Azure, and Google Cloud, and platforms like Snowflake, BigQuery, Redshift, Databricks, and Synapse. For orchestration and transformations, we use tools such as Airflow, dbt, and cloud-native services. However, vendor-agnostic and choose what fits your goals. Through our comprehensive data engineering services, we ensure your stack is scalable, maintainable, and aligned with your team’s capabilities.
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How long does a typical data engineering project take?
Timelines vary based on scope, number of data sources, and existing data infrastructure. A focused assessment may take a few sprints, while multi-domain transformations can span several months. Regardless of the size of the project, with our data engineering consulting services, we break delivery into clear, incremental phases so you start seeing value early through prioritized datasets and dashboards.
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Can you work with my existing analysts and engineering team?
Yes. Syndicode’s approach is collaborative by design. We typically pair our data engineering specialists and architects with your product owners, analysts, and software engineers. Together, we define data contracts, metrics, and responsibilities. This knowledge sharing ensures the new platform reflects how your business actually works and that your team can extend it later. Our goal is to empower your people through top-tier data science engineering services, not replace them.
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How do you ensure data security and regulatory compliance?
Security and compliance are built into our designs. We apply principles such as least-privilege access, encryption in transit and at rest, network segmentation, and audit logging. We also help you manage PII correctly, implement data retention policies, and support GDPR-aligned practices. Our experience from enterprise software development and regulated industries allows us to deliver comprehensive data engineering services across regulated industries and ensures your data platform meets both technical and legal expectations.
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What happens after the initial implementation is complete?
After launch, you can continue to work with Syndicode as a long-term data engineering partner or take full ownership internally. We offer flexible support options: on-demand data engineering consulting services, a smaller maintenance team, or scheduled health checks. We also provide training, documentation, and architectural guidelines so your platform remains robust as new products, markets, and regulations appear. This reduces long-term risk and protects your investment in data.