AWS Data Engineer

Role: AWS Data Engineer Location: Remote(United States) Required Skills: • Hands-on experience with AWS services such as S3, Redshift, Glue, DMS, and Lambda • Strong knowledge of data warehousing and cloud analytics architectures • Advanced SQL for data transformation, validation, and optimization • Proficiency in Python or Java for data engineering and automation • Solid understanding of ETL frameworks and data modeling principles • Experience working in regulated or large enterprise environments • Understanding of data governance, security, and compliance requirements • Ability to design resilient, production-grade data platforms • Strong analytical and problem-solving skills • Excellent communication and cross-functional collaboration abilities • Ability to work effectively with technical and non-technical stakeholders • Experience supporting energy, utilities, or infrastructure analytics • Exposure to grid modernization, asset analytics, or operational data platforms • AWS certifications (e.g., AWS Certified Data Analytics – Specialty) Responsibilities: • Design and maintain AWS-based data platforms supporting utility operations, grid analytics, and enterprise reporting • Build scalable data pipelines and data stores to support operational, asset, and customer data • Optimize architectures for reliability, resiliency, and cost efficiency consistent with utility standards • Develop ETL pipelines using AWS services to ingest data from utility source systems, operational platforms, and enterprise applications • Support near real time and batch data processing for analytics and reporting use cases • Ensure data lineage and traceability across systems • Design dimensional and analytical data models to support grid reliability, asset performance, and operational insights • Enable analytics and visualization use cases by providing clean, well-structured datasets • Partner with analytics teams to support cloud-based analytics initiatives • Implement strong data security controls including encryption, IAM policies, and access governance • Ensure compliance with regulatory, audit, and internal governance requirements typical of utility environments • Support data quality, retention, and auditability standards • Establish automated data validation, monitoring, and error-handling mechanisms • Ensure accuracy, completeness, and consistency of enterprise and operational data • Proactively identify and resolve pipeline and performance issues • Collaborate with utility IT teams, data scientists, business analysts, and operations stakeholders • Translate business and operational requirements into scalable technical solutions • Provide technical guidance on AWS data engineering best practices • Stay current with AWS innovations relevant to energy and utilities • Recommend improvements aligned with cloud modernization and analytics strategy • Contribute to standardization and reusable data engineering frameworks Regards Praveen Kumar R (Praveen) Talent Acquisition Group – Strategic Recruitment Manager praveen.r@themesoft.com| Themesoft Inc