Job Description Insight Global is seeking an experienced ETL/Pipeline Engineer to support a large-scale initiative focused on modernizing and scaling data pipeline capabilities across our client's retail technology ecosystem. This individual will provide hands-on engineering support across data ingestion, transformation, validation, orchestration, and downstream analytics workflows that support critical business operations and high-volume data processing. Day-to-day responsibilities include translating business requirements, source-to-target mappings, data contracts, and schema requirements into scalable ETL logic; building and optimizing Spark-based processing jobs using Python, PySpark, Spark SQL, and SQL; migrating and validating existing data pipelines; performing data quality checks, reconciliation, functional testing, integration testing, regression testing, and performance testing; and supporting job scheduling, dependency management, monitoring, troubleshooting, and production readiness activities. This person will partner closely with data engineering, QA, DevOps, architecture, product, analytics, and business stakeholders to manage technical risks, resolve blockers, maintain documentation, support deployment readiness, and ensure reliable delivery of production-ready data solutions. The ideal candidate will have a strong background in ETL development and data pipeline engineering, experience working in complex enterprise environments, and the ability to stay hands-on while driving pipelines through development, testing, release readiness, production support, and operational handoff. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.

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• 5+ years of professional experience in ETL development, data pipeline engineering, data integration, or enterprise data processing.
• Strong hands-on experience with Python, PySpark, Spark SQL, SQL, and distributed data processing frameworks.
• Experience building and supporting batch data pipelines, file-based ingestion, source-to-target mapping, transformation logic, schema validation, and data reconciliation.
• Experience with orchestration, job scheduling, dependency management, retries, error handling, logging, monitoring, alerting, and troubleshooting.
• Working knowledge of data quality validation, contract testing, functional testing, integration testing, regression testing, performance testing, and defect remediation.
• Experience with version control, CI/CD concepts, code reviews, deployment readiness, documentation, and agile delivery.
• Strong communication skills and ability to work cross-functionally with engineering, QA, DevOps, product, and business stakeholders.
• Experience with GCP, BigQuery, AWS, Azure, or other cloud data platforms.
• Exposure to Kafka, NoSQL platforms, data lake architecture, cloud storage, data warehouse platforms, or managed distributed processing services.
• Experience migrating legacy ETL jobs, refactoring pipelines, tuning Spark jobs, or improving pipeline reliability.
• Familiarity with data governance, lineage, metadata, schema evolution, access management, and audit-ready documentation.
• Certifications or training in data engineering, cloud platforms, Spark, DevOps, agile delivery, or quality engineering.