Senior Data Engineer

Senior Data Engineer

The role involves working closely with cross-functional teams including data scientists, analysts, architects, and public sector stakeholders to enable data-driven decision-making and ensure the accuracy, consistency, and security of large-scale datasets.

Key Responsibilities:

• Lead the end-to-end design, development, and maintenance of scalable data pipelines and ETL/ELT workflows.
  
• Develop data models, metadata systems, and data quality frameworks.
  
• Integrate data from diverse sources (e.g., APIs, RDBMS, flat files, cloud services) into unified formats aligned with project requirements.
  
• Ensure adherence to government data security, privacy, and compliance standards.
  
• Collaborate with data architects and application teams on schema design, query optimization, and performance tuning.
  
• Support data governance, cataloging, and lineage initiatives.
  
• Monitor pipeline performance and troubleshoot issues across batch and real-time data workflows.
  
• Document processes, data flows, and architectural decisions.
  

Required Qualifications:

• 7+ years

  of professional experience in data engineering, data integration, and data quality management.
• Hands-on experience with big data technologies (e.g., Hadoop, Spark, Hive), modern data warehouses (e.g., Snowflake, BigQuery, Redshift), and cloud platforms (AWS, Azure, GCP).
  
• Proficiency in SQL, Python, and ETL tools (e.g., Apache NiFi, Talend, Informatica).
  
• Expertise in implementing data quality frameworks, validation checks, and exception handling.
  
• Strong understanding of data modeling (both OLTP and OLAP), data lakes, and data governance principles.