Energy Domain is a must.
Under 7 years of experience only.
Permanent.
Key Responsibilities
Design, develop, and maintain data ingestion pipelines using open-source frameworks and tools
Build and optimise ETL/ELT processes to handle small to large-scale data processing requirements
Develop data models and schemas that support analytics, business intelligence and product needs
Monitor, troubleshoot, and optimise data pipeline performance and reliability
Collaborate with stakeholders, analysts and product team to understand data requirements
Implement data quality checks and validation processes to ensure data integrity
Participate in architecture decisions and contribute to technical roadmap planning
Technical Skills:
Great SQL skills with experience in complex query optimization
Strong Python programming skills with experience in data processing libraries (pandas, NumPy, Apache Spark)
Hands-on experience building and maintaining data ingestion pipelines
Proven track record of optimising queries, code, and system performance
Experience with open-source data processing frameworks (Apache Spark, Apache Kafka, Apache Airflow)
Knowledge of distributed computing concepts and big data technologies
Experience with version control systems (Git) and CI/CD practices
Experience with relational databases (PostgreSQL, MySQL or similar)
Experience with containerization technologies (Docker, Kubernetes)
Experience with data orchestration tools (Apache Airflow or Dagster)
Understanding of data warehousing concepts and dimensional modelling
Understanding of cloud platforms using infrastructure-as-code (IaC) approaches
Knowledge of streaming data processing and real-time analytics
Experience with data quality and monitoring tools
Preferred Qualifications:
Bachelor's degree in Computer Science, Engineering, Mathematics, or related field
2-5 years of experience in data engineering or related roles
Experience working in the Energy industry