ETL Developer
About The Position
We are seeking an experienced ETL Developer to design, develop, and optimize enterprise-scale data integration solutions supporting business intelligence, analytics, regulatory reporting, and cloud data modernization initiatives. This role focuses on building high-performance ETL pipelines that ingest, transform, validate, and deliver data from diverse operational systems into enterprise data warehouses and cloud-based analytics platforms. You will collaborate with data architects, data engineers, business analysts, cloud engineers, and BI developers to develop scalable data integration frameworks, automate complex workflows, and ensure the delivery of high-quality, trusted data across the organization. The ideal candidate combines strong ETL development expertise with advanced SQL skills, cloud data platform experience, and a deep understanding of data warehousing and enterprise data governance.
Requirements
- Five or more years of professional experience developing enterprise ETL solutions.
- Strong hands-on experience with ETL platforms such as Informatica PowerCenter, SSIS, Talend, IBM DataStage, or Pentaho.
- Advanced SQL development skills with SQL Server, Oracle, PostgreSQL, Snowflake, or Teradata.
- Strong understanding of relational databases, dimensional modeling, star schema, snowflake schema, and data warehousing principles.
- Experience designing ETL workflows involving complex transformations, joins, aggregations, lookups, and data validation.
- Hands-on experience implementing Change Data Capture (CDC), Slowly Changing Dimensions (SCD Type 1 & Type 2), and incremental loading techniques.
- Experience working with cloud data platforms including Azure Data Factory (ADF), AWS Glue, or Google Cloud Data Fusion.
- Experience integrating structured and semi-structured data formats including JSON, XML, CSV, Parquet, and Avro.
- Familiarity with scripting languages such as Python, PowerShell, or Shell scripting for ETL automation.
- Experience scheduling workflows using Control-M, Autosys, Apache Airflow, Azure Data Factory, or enterprise schedulers.
- Experience with Git, Azure DevOps, Jenkins, or other CI/CD tools for ETL deployments.
- Strong debugging, troubleshooting, and ETL performance tuning skills.
- Experience working with Agile Scrum teams and enterprise SDLC processes.
Nice To Haves
- Experience with cloud data warehouses including Snowflake, Azure Synapse Analytics, Amazon Redshift, or Google BigQuery.
- Knowledge of Apache Spark, Databricks, PySpark, or distributed data processing frameworks.
- Experience implementing enterprise Master Data Management (MDM) and Data Quality solutions.
- Familiarity with streaming technologies including Apache Kafka, Azure Event Hub, or Amazon Kinesis.
- Experience developing metadata-driven ETL frameworks and reusable integration components.
- Knowledge of Data Vault 2.0 architecture and modern data lakehouse concepts.
- Familiarity with DevOps practices for data engineering and automated ETL deployments.
- Experience with BI platforms including Power BI, Tableau, or Qlik for downstream reporting integration.
- Understanding of data governance frameworks, lineage, cataloging, and regulatory compliance.
- Cloud certifications in Azure, AWS, Snowflake, or Informatica are highly desirable.
Responsibilities
- Design, develop, and maintain enterprise ETL/ELT pipelines for large-scale data integration projects.
- Build scalable data ingestion workflows that extract data from relational databases, cloud applications, APIs, flat files, and enterprise systems.
- Develop transformation logic for cleansing, standardizing, validating, and enriching large datasets.
- Design and optimize batch and near real-time data processing pipelines supporting business-critical reporting and analytics.
- Implement Slowly Changing Dimensions (SCD), Change Data Capture (CDC), incremental loading strategies, and data reconciliation processes.
- Develop reusable ETL frameworks, metadata-driven workflows, and parameterized jobs to improve maintainability.
- Perform source-to-target mapping, data profiling, and data quality analysis during project implementation.
- Optimize ETL job performance by improving SQL queries, partitioning strategies, indexing, and parallel processing.
- Monitor ETL workflows, troubleshoot production failures, and implement proactive alerting and recovery mechanisms.
- Collaborate with cloud engineers to migrate legacy ETL workloads to Azure or AWS cloud platforms.
- Participate in data architecture discussions, code reviews, deployment planning, and production support.
- Ensure data security, governance, auditability, and regulatory compliance across enterprise data pipelines.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
