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 LaTronic Solutions client work. Specific client requirements, schedules, security requirements, clearances, and other project details may vary by engagement.
LaTronic Solutions is committed to a professional and inclusive workplace. Employment decisions are based on qualifications, merit, business need, and the requirements of the applicable engagement.
