ETL Development and Data Integration Services
Transform your data infrastructure with expert ETL development services. Custom data extraction, transformation, and loading solutions for enterprise data warehouses, analytics platforms, and real-time processing.
Hire TYMIQ experts
Platform-agnostic expertise: Talend, Informatica, Apache NiFi, SSIS, custom solutions
Flexible engagement models: dedicated teams, staff augmentation, project-based delivery
Quick project start within 2-4 weeks from requirements finalization
Why leverage professional ETL development for your business
TYMIQ specializes in building enterprise-grade ETL infrastructure that handles the full data integration lifecycle. From extraction across heterogeneous sources to transformation with rigorous quality controls to loading into analytics-ready formats—we create pipelines that scale with your business and ensure data reliability.
The current state of ETL in modern data architectures
ETL (Extract, Transform, Load) remains essential to modern data infrastructure alongside newer approaches like ELT. As data volumes expand and integration requirements grow more complex, organizations continue to prioritize ETL solutions for their proven reliability in managing enterprise data workflows.
Expected to reach $15.2B by 2028 (growing at 10.7% CAGR)
68% of enterprises are moving ETL workloads to cloud platforms
54% of organizations are implementing streaming ETL pipelines
focus:
Modern businesses generate data from dozens or hundreds of sources—databases, SaaS applications, IoT devices, APIs, and file systems. ETL processes ensure this disparate data is consolidated, cleaned, transformed, and made available for analytics, machine learning, and operational systems. Without robust ETL, organizations struggle with data silos, inconsistent reporting, and poor data quality.
When to implement ETL solutions for your data infrastructure
ETL development is essential for many data scenarios, but it's critical to understand when ETL is the right approach versus alternatives like ELT or reverse ETL. Here's when professional ETL development delivers maximum value:
When building centralized data warehouses or analytics platforms, ETL ensures data from multiple operational systems is properly extracted, cleaned, transformed, and structured for analytical queries and reporting.
Organizations with legacy systems (mainframes, AS/400, old ERP systems) need ETL to extract data from these systems and integrate with modern cloud platforms, applications, or data warehouses without disrupting operations.
During mergers, acquisitions, or system upgrades, ETL processes enable safe migration of historical data, consolidation of multiple databases, and preservation of data integrity across environments.
When business operations require up-to-the-minute data across systems - customer data, inventory levels, pricing - real-time or micro-batch ETL ensures consistent, synchronized information.
Creating a single source of truth for critical business entities (customers, products, suppliers) requires sophisticated ETL processes to consolidate, deduplicate, and maintain golden records from multiple source systems.
Industries with strict compliance requirements (finance, healthcare, insurance) use ETL to ensure accurate, auditable data pipelines for regulatory reporting, with proper data lineage and quality controls.
Organizations running hybrid or multi-cloud infrastructures need ETL to seamlessly move and synchronize data across on-premise systems, AWS, Azure, GCP, and SaaS applications.
When poor data quality impacts business operations, specialized ETL processes implement validation rules, standardization, deduplication, and enrichment to improve overall data quality.
Custom ETL development services we provide
As an ETL development company, TYMIQ offers comprehensive data integration services across platforms and technologies. Our team has extensive experience building scalable ETL solutions that meet enterprise requirements for performance, reliability, and data quality.
We design and build custom ETL pipelines tailored to your specific data sources, transformation logic, and target systems, from simple batch jobs to complex multi-stage workflows with error handling and recovery.
End-to-end data warehouse development including dimensional modeling, ETL pipeline creation, incremental load strategies, slowly changing dimensions (SCD), and star/snowflake schema implementation.
Development of real-time data integration using streaming technologies (Apache Kafka, AWS Kinesis), change data capture (CDC), micro-batch processing, and event-driven architectures for time-sensitive data.
Implementation of comprehensive data quality frameworks, including profiling, validation rules, standardization, deduplication, data enrichment, and quality monitoring with alerting.
Seamless integration with cloud data platforms (Snowflake, Redshift, BigQuery, Azure Synapse), cloud storage (S3, Azure Blob, GCS), and cloud-native ETL tools (AWS Glue, Azure Data Factory).
Expert integration of legacy systems, including mainframes, AS/400, Oracle EBS, SAP, and proprietary databases,s using modern ETL approaches, APIs, or direct database connectivity.
Migration from legacy ETL tools to modern platforms, re-engineering outdated processes, performance optimization, and cloud migration of existing ETL workloads.
Building ETL processes that consume REST/SOAP APIs, integrate with microservices architectures, implement API orchestration, and handle complex authentication/authorization.
Analysis and optimization of existing ETL processes, identifying bottlenecks, implementing parallel processing, partitioning strategies, and incremental load patterns to improve performance.
Have questions? Our data engineering team is ready to assist you.
Schedule a callTech stack for Talend development we use
We utilize the complete Talend ecosystem along with complementary technologies to deliver robust, scalable data integration solutions that meet enterprise requirements.
We have deep expertise across commercial and open-source ETL platforms.
Talend data integration
Informatica PowerCenter / Cloud
Microsoft SSIS
(SQL Server Integration Services)
Oracle
IBM DataStage
SAP Data Services
Apache NiFi
Apache Airflow
AWS Glue
Azure Data Factory
Google Cloud Dataflow
Python
(pandas, PySpark, SQLAlchemy)
Java/Scala
(for Spark jobs)
SQL stored procedures
Shell scripting
Comprehensive connectivity across all major database platforms
Oracle database
SQL Server
PostgreSQL
MySQL
IBM DB2
Snowflake
Amazon Redshift
Google BigQuery
Azure Synapse
Databricks
MongoDB
Cassandra
Redis
Elasticsearch
HBase
Amazon DynamoDB
Scalable processing for large data volumes
Apache Hadoop
(HDFS, Hive, HBase)
Apache Spark
Apache Kafka
Apache Flink
AWS EMR
Azure HDInsight
Google Dataproc
Full-stack cloud data integration capabilities
Amazon S3
RDS
Redshift
Glue
EMR
AWS Kinesis
AWS Lambda
Data Pipeline
DMS
Blob Storage
Azure SQL
Azure Synapse
Data Factory
HDInsight
Event Hubs
Cloud SQL
Cloud Storage
BigQuery
Dataflow
Dataproc
Pub/Sub
Cloud Composer
Ensuring data accuracy and compliance
Automated deployment and workflow management
Apache Airflow
Jenkins
GitLab
Kubernetes
Docker
Terraform
CloudFormation
Ansible
Git version control
Prometheus
Grafana
ELK Stack
Datadog
Graylog
Instana
When to consider ETL migration or modernization
If your ETL jobs take hours to complete, miss SLA windows, or can't keep up with growing data volumes, it's time to modernize. Modern ETL platforms offer parallel processing, cloud scalability, and optimization capabilities.
Legacy ETL tools often have expensive per-core or per-server licensing. Migrating to open-source platforms (Talend, Apache NiFi) or cloud-native tools (AWS Glue, Azure Data Factory) can reduce costs by 50-70%.
If your current ETL platform struggles with cloud data sources, SaaS applications, or modern cloud warehouses (Snowflake, BigQuery), migration to cloud-native or cloud-enabled tools is essential.
Legacy ETL systems built on outdated platforms or custom code become maintenance nightmares when developers leave. Modern ETL tools offer better documentation, visual development, and larger talent pools.
Batch-only ETL can't meet modern business needs for real-time analytics, operational dashboards, or immediate data synchronization. Streaming ETL platforms enable near-real-time data processing.
If data quality issues persist despite ETL processes, it's time to implement modern data quality frameworks, validation rules, and comprehensive data governance with proper lineage tracking.
When vendors discontinue products or end support for versions you're using, proactive migration prevents future crises and security vulnerabilities.
If your ETL infrastructure can't scale to handle increasing data volumes, new data sources, or an expanding user base without significant hardware investments, cloud-based or distributed ETL is the answer.
Ready to modernize? Transform your legacy ETL infrastructure with our migration expertise.
Talk to our data engineering expertsOur featured ETL projects
With a decade of data integration experience, TYMIQ has built scalable ETL solutions for organizations of all sizes - from fast-growing startups to Fortune 500 enterprises - across multiple industries, consistently achieving over 95% client satisfaction.
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Using Talend-based ETL processes, TYMIQ built a scalable data integration layer for Conrad’s sourcing platform, connecting diverse systems like SAP, Stibo STEP, Bazaarvoice, and others into a unified data flow. Automated data extraction, transformation, and delivery pipelines power millions of product records and enable self-service feed creation through the Conrad Data Centrifuge portal.
Let's explore how we can optimize your data integration infrastructure.
Drop us a message, and we will find the right ETL solution for you.
ETL development services for your business
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Small-to-medium businesses (SMBs)
SMBs often struggle with data scattered across multiple systems, manual reporting processes, or the need to replace spreadsheet-based workflows with automated data pipelines. TYMIQ serves as a reliable partner for ETL development, providing cost-effective solutions using open-source tools and cloud platforms without the overhead of enterprise licenses.
Enterprise companies
We understand the challenges faced by large organizations: complex data landscapes, legacy system integration, strict compliance requirements, and limited internal data engineering resources. We offer flexible engagement - whether augmenting your existing team, taking ownership of specific ETL workloads, or executing large-scale data warehouse and migration projects.
Custom ETL solutions for industries
How we ensure ETL solution quality
We implement multi-layered data quality checks, including row counts, column-level validation, referential integrity, business rule validation, and statistical anomaly detection. Quality metrics are tracked and reported automatically.
Every ETL pipeline undergoes rigorous unit testing, integration testing, and end-to-end validation. We verify data transformation logic, test edge cases, validate data volumes, and ensure error handling works as expected before production deployment.
All ETL code and pipeline configurations undergo peer review to ensure adherence to coding standards, maintainability, and alignment with architectural patterns. We document design decisions and transformation logic.
We design ETL processes with performance in mind from the start: parallel processing, incremental loads, partitioning strategies, indexing optimization, and resource-efficient transformations. Every pipeline is load-tested before production.
We implement comprehensive monitoring covering job execution status, data volumes, processing times, error rates, and data quality metrics. Automated alerts notify teams of failures or anomalies requiring attention.
We maintain thorough documentation, including technical design documents, data mapping specifications, data dictionaries, operational runbooks, and troubleshooting guides. Knowledge transfer sessions ensure your team can maintain solutions.
Why choose TYMIQ for ETL development
Choosing TYMIQ for your ETL development needs ensures seamless integration with your business environment and effective handling of complex data integration challenges. Here's why TYMIQ stands out:
TYMIQ has deep experience across commercial ETL tools (Informatica, SSIS, Talend Enterprise), open-source platforms (Apache NiFi, Airflow), and cloud-native services (AWS Glue, Azure Data Factory). We recommend and implement the best fit for your requirements and budget.
We quickly scale our data engineering team according to your project's needs—from single ETL developer augmentation to full project teams handling enterprise-wide data warehouse implementations.
Our data engineers focus exclusively on your ETL initiatives, ensuring deep understanding of your data landscape, business logic, and integration requirements. This guarantees consistent quality and faster delivery.
Beyond ETL development, our team brings expertise in data modeling, database optimization, data quality, analytics, and BI integration—ensuring your ETL pipelines fit into a cohesive data strategy.
We're genuinely invested in your data initiatives' success, bringing proactive problem-solving and continuous optimization. We don't just build ETL pipelines—we ensure they deliver business value.
Your ETL project kicks off within 2-4 weeks. Our efficient discovery process, pre-built frameworks, and experienced team enable rapid project initiation and value delivery.
We offer clear, competitive pricing models: time & materials, fixed-price projects, or dedicated team engagements. No hidden costs, transparent estimates, and flexible contracts.
Streamline your data integration by eliminating bottlenecks and data silos with TYMIQ's expert ETL development services.
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