Remote Data Enigneer

Technologies / Skills:

• Strong hands-on experience with AWS data engineering services (ETL, orchestration, and streaming tools.
• Proficiency in SQL, Python (Pandas, NumPy) and PySpark.
• Experience in ETL/ELT pipeline development, data modeling and working with large-scale data systems.
• Familiarity with CI/CD workflows, Git and version control practices.

Responsibilities:

• Collaborate with business stakeholders and technical teams to gather requirements and translate them into scalable data solutions.
• Design, build and maintain robust, secure, high-performance data pipelines
• Ensure adherence to data quality, governance and compliance standards
• Work with architects and engineering leads to follow best practices and optimize for performance
• Communicate insights and technical decisions effectively with cross-functional stakeholders
• Participate in Agile ceremonies and deliver iterative improvements in data infrastructure

Required Qualifications:

• 3+ years of hands-on experience with AWS data engineering services, including:
• AWS Glue, Athena, EMR, Redshift, Lambda, Kinesis, S3, Step Functions, CloudWatch.
• Expertise in building data pipelines using PySpark/Spark SQL.
• Strong SQL and Python skills with experience in large-scale data transformation and ingestion.
• Knowledge of Spark internals (joins, partitioning, memory management) and performance tuning via Spark UI.
• Experience with Git, CI/CD pipelines, and working in Agile environments.
• Understanding of partitioning, schema design, and query performance optimization.

Desired Qualifications:

• Experience with workflow orchestration tools like Apache Airflow or AWS Step Functions.
• Exposure to streaming platforms such as Kafka, Kinesis etc .
• Working knowledge of AWS SDKs (e.g., Boto3) for automation and integration.
• Familiarity with modern ETL/ELT patterns and data modeling techniques.
• Basic proficiency in shell scripting for automation and support tasks.