Senior Data Engineer

Role & responsibilities

About the Role

We are seeking a highly skilled Senior Data Engineer to design, develop, and optimize our data systems

and pipelines. The ideal candidate will have strong expertise in SQL, Python, AWS, and Tableau, and a

passion for transforming raw data into actionable insights that drive business decisions.

Key Responsibilities

• Design, build, and maintain scalable ETL / ELT data pipelines for ingestion, transformation, and

storage.

• Work with business stakeholders to identify data requirements and translate them into effective

data solutions.

• Develop and optimize SQL queries, stored procedures, and data models for high performance.
• Implement data integration solutions using AWS services such as S3, Glue, Redshift, Lambda,

and RDS.

• Collaborate with analysts and business users to enable data visualization and reporting in

Tableau.

• Ensure data accuracy, quality, and consistency through validation, testing, and monitoring.
• Automate workflows and data quality checks using Python scripting.
• Support data governance, documentation, and adherence to security and compliance standards.

Required Skills & Qualifications

• Bachelors or Master’s degree in Computer Science, Information Technology, or related field.
• 5+ years of hands-on experience in Data Engineering or similar roles.
• Strong expertise in SQL for data extraction, transformation, and optimization.
• Proficiency in Python for data manipulation, automation, and scripting.
• Solid experience with AWS cloud ecosystem (S3, Glue, Redshift, Lambda, IAM, etc.).
• Hands-on experience with Tableau for dashboard development and data visualization support.
• Deep understanding of data warehousing, modeling, and ETL design patterns.
• Strong problem-solving skills and ability to work in agile, collaborative environments.

Good to Have

• Experience with Airflow or other workflow orchestration tools.
• Exposure to Snowflake, Athena, or Data Lake architectures.
• Knowledge of API integration and data streaming tools (Kafka, Kinesis).
• Understanding of CI/CD, Git, and modern DevOps practices in data environments.