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