Data Engineer

Summary

The Data Engineer will build and maintain scalable ETL/ELT workflows using Informatica, Python, and SQL to manage data within Google BigQuery. The role involves migrating legacy on-premise assets to the cloud and optimizing data pipeline performance.

  • Build and maintain scalable data extraction, transformation, and loading workflows using Informatica
  • Manage tables, datasets, partitions, and clustering inside Google BigQuery for large-scale analytics.
  • Write and tune advanced SQL scripts and queries to boost execution speed and lower compute costs.
  • Use Unix shell scripting to automate file transfers, pre- and post-load routines, and batch job sequencing.
  • Develop custom Python scripts to parse files, orchestrate data movement, and interact with cloud APIs.
  • Schedule, monitor, and troubleshoot integrated workflows across Unix cron jobs and cloud schedulers.
  • Move legacy on-premise data assets into cloud environments via hybrid ETL pipelines.
  • Implement error-handling, logging, and data validation rules using SQL and Python checks.
  • Diagnose bottlenecks in Informatica mappings, BigQuery queries, and shell scripts.
  • Maintain technical mapping specs, system architecture diagrams, and partner with analysts or data

Key Skills & Experience

  • 4-7 years of hands-on data engineering experience designing, developing, and supporting production data pipelines.
  • Experience building ETL/ELT workflows using Informatica, including mapping development, workflow scheduling, monitoring, and troubleshooting.
  • Proven capability working with Google BigQuery, including dataset management, table design, partitioning, clustering, and query performance optimisation.
  • Advanced SQL skills, including complex joins, window functions, stored procedures, query tuning, and data validation routines.
  • Practical experience with Unix shell scripting for file handling, batch orchestration, job sequencing, and automation of operational tasks. (desired)
  • Proficiency in Python for data processing, file parsing, API integration, automation, and development of reusable data engineering utilities.
  • Experience supporting cloud migration or hybrid data integration initiatives, including movement of legacy on-premise data assets to cloud platforms. (desired)
  • Good understanding of data quality, reconciliation, error handling, logging, and operational monitoring practices across batch and scheduled workloads.
  • Ability to diagnose and resolve technical issues across Informatica mappings, SQL queries, shell scripts, and cloud data pipelines.
  • Experience maintaining technical documentation, mapping specifications, operational runbooks, and working closely with analysts, testers, and business stakeholders.
  • Familiarity with Agile delivery practices, code version control, release processes, and collaborative delivery across onshore and offshore teams.
  • Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related discipline; relevant cloud, data, or Informatica certifications are desirable.

See also

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