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
