Data Engineer

We are seeking a skilled and motivated Data Engineer to join our client's dynamic team. As a Data Engineer, you will play a critical role in designing, building, and maintaining data pipelines and architectures that support business intelligence, analytics, and operational needs. You will collaborate with cross-functional teams to ensure data is accessible, reliable, and secure, enabling data-driven decision-making across the organization.

Key Responsibilities

• Advise stakeholders on data strategy by leveraging a consultative approach to assess current data landscapes, identify gaps, and recommend best-fit solutions that align with business objectives.
• Design, develop, and maintain scalable ETL/ELT pipelines that support analytics, machine learning, and operational workloads.
• Build and optimize data models, including dimensional models, data lakes, and data warehouse structures.
• Develop real‑time and batch data ingestion processes using modern data engineering frameworks.
• Ensure high data quality through validation, monitoring, and automated testing.
• Collaborate with cross‑functional partners to translate business requirements into data solutions.
• Implement data governance, security controls, and privacy best practices.
• Optimize data systems for performance, reliability, and cost‑efficiency in cloud environments.
• Troubleshoot, diagnose, and resolve data-related issues across distributed systems.
• data workflows, architecture, and best practices.

• Bachelors degree in Computer Science, Information Systems, Engineering, or a related field (Masters preferred).
• 2+ years of experience in data engineering, database management, or a related field.
• Strong proficiency in SQL and Pyspark
• Experience with ETL tools, data integration frameworks, and cloud platforms (e.g., Azure, AWS, GCP, Oracle Cloud).
• Strong knowledge of relational and non-relational databases
• Familiarity with data modeling, data warehousing, and big data technologies.
• Hands‑on experience with ETL/ELT frameworks (e.g., Airflow, dbt, Glue, Dataflow).
• Experience in the energy or utilities industry.
• Knowledge of cybersecurity best practices for data environments.
• Understanding of regulatory compliance (e.g., NERC CIP, GDPR) as it relates to data management.