Position Overview
Builds and operates secure, reliable data pipelines that ingest, transform, validate, deliver, and monitor data across source systems and cloud data platforms.
Key Responsibilities
- Design and build batch, near-real-time, and streaming data pipelines using Azure Data Factory, Databricks, Airflow, AWS Glue, Dataflow, Informatica, Talend, or comparable platforms.
- Develop ETL/ELT logic, data transformations, mappings, data-cleansing processes, validations, and reconciliation procedures.
- Implement CDC, API-based integration, file transfer, database replication, event-driven ingestion, and data-orchestration workflows.
- Monitor pipeline performance, job failures, data quality, timeliness, and operational incidents.
- Build automated tests, data-quality checks, error-handling routines, alerting, and recovery mechanisms.
- Support legacy-to-cloud data migration, cutover, reconciliation, and post-migration validation.
Minimum Qualifications
4+ years in data engineering, ETL development, database integration, analytics engineering, or systems integration. Strong SQL plus Python, Spark, Scala, Java, or comparable data-engineering skills. Azure Data Engineer, Databricks, Snowflake, AWS Data Analytics, or similar certification preferred.
About This Opportunity
This is a full-time remote position supporting current and upcoming JJT & Associates client work. Specific client requirements, schedules, security requirements, clearances, and other project details may vary by engagement.
JJT & Associates is committed to a professional and inclusive workplace. Employment decisions are based on qualifications, merit, business need, and the requirements of the applicable engagement.