Senior Data Engineer

Data Engineer

Job Summary

We are seeking an experienced Data Engineer with 6+ years of hands-on experience in designing, developing, and maintaining enterprise data solutions. The ideal candidate will have strong expertise in ETL/ELT development, data integration, and modern data engineering practices. You will work closely with business stakeholders, analytics teams, and data scientists to build scalable, high-performance data pipelines that support reporting, analytics, and AI-driven initiatives.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for enterprise data processing and analytics.
• Perform data ingestion, transformation, cleansing, and integration across multiple data sources and business domains.
• Build and optimize data pipelines to ensure high performance, reliability, and scalability.
• Support ongoing data engineering operations, production support, and reporting workflows.
• Collaborate with business, analytics, and cross-functional teams to understand data requirements and deliver robust data solutions.
• Enable investigative analytics for business use cases such as fraud detection, waste reduction, and operational insights.
• Work with modern data engineering and analytics tools to accelerate data discovery and ensure data accuracy.
• Monitor and improve data quality, governance, reliability, and pipeline performance.
• Participate in data model design, workflow optimization, and continuous process improvements.
• Support both production and non-production environments while adhering to operational best practices.
• Troubleshoot data issues and perform root cause analysis for pipeline failures.

Required Skills & Experience

• 6+ years of experience in Data Engineering with strong ETL/ELT development expertise.
• Strong experience with SQL and relational databases.
• Hands-on experience with Python or Scala for data processing.
• Experience building and maintaining ETL/ELT pipelines using modern data integration tools.
• Strong understanding of data warehousing concepts and dimensional modeling.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
• Knowledge of distributed data processing frameworks such as Apache Spark.
• Experience with orchestration tools like Apache Airflow, Azure Data Factory, or similar.
• Familiarity with version control systems such as Git.
• Strong understanding of data quality, data governance, and performance optimization.
• Experience supporting enterprise reporting and analytics solutions.
• Exposure to AI-enabled analytics and modern data exploration tools is a plus.
• Excellent analytical, problem-solving, and communication skills.

Work Location: Remote