CES has 26+ years of experience in delivering Software Product Development, Quality Engineering, and Digital Transformation Consulting Services to Global SMEs & Large Enterprises. CES has been delivering services to some of the leading Fortune 500 Companies including Automotive, AgTech, Bio Science, EdTech, FinTech, Manufacturing, Online Retailers, and Investment Banks. These are long-term relationships of more than 10 years and are nurtured by not only our commitment to timely delivery of quality services but also due to our investments and innovations in their technology roadmap. As an organization, we are in an exponential growth phase with a consistent focus on continuous improvement, process-oriented culture, and a true partnership mindset with our customers. We are looking for the right qualified and committed individuals to play an exceptional role as well as to support our accelerated growth. You can learn more about us at: http://www.cesltd.com/
About the Role:
We are seeking a highly experienced Senior Data Engineer with good experience working with RDMBS systems and Data modeling. The ideal candidate should have deep expertise in data modeling, schema design, ETL/data engineering, and data quality best practices, with proven experience handling large-scale structured and unstructured datasets.
Key Responsibilities:
Analyze and interpret complex schemas across multiple source system databases to support migration and integration requirements.
Develop conceptual, logical, and physical data models aligned with business rules, performance expectations, and regulatory constraints.
Define entity relationships, primary/foreign key structures, indexing strategies, and normalization/denormalization approaches.
Collaborate with product SMEs to map configuration and transactional datasets for a structured two‑phase migration process.
Establish robust validation frameworks covering schema compatibility, data type integrity, truncation detection, and referential consistency.
Design and build scalable, reliable data pipelines to support warehousing, analytics, and migration workflows.
Apply core data engineering principles—data modeling, partitioning, indexing, and performance tuning—independent of specific tools or technologies.
Troubleshoot data and pipeline issues efficiently and operate independently with minimal supervision.
Leverage cloud platforms (AWS, Azure, or GCP) for data services, storage, and compute infrastructure as needed.
Required Skills & Qualifications:
8–10 years of experience in Data Engineering, with strong expertise in data modeling and relational database systems.
Advanced proficiency in SQL, including hands‑on experience with query optimization and performance tuning.
Excellent analytical, problem‑solving, and debugging abilities.
Deep understanding of data quality frameworks and experience building enterprise‑grade, scalable data pipelines.
Strong communication and collaboration skills, with the ability to work effectively across teams and stakeholders.