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/
We are seeking an enthusiastic and highly skilled Senior Data Engineer to play an instrumental role in creating and evolving complex data-centric solutions that improve decision making for our clients and internal staff.
You will be part of a data engineering team responsible for building and maintaining scalable data systems and pipelines. The team manages acquisition, storage, and processing of data from internal and external sources for multiple analytical products. This includes data mapping, geocoding, validation, metadata management, and automation processes. The team uses Python scripting to implement and automate data workflows on top of relational and columnar databases.
In this role, you will design and optimize data infrastructure, ensuring the reliability, scalability, and performance of our platforms. You will collaborate with stakeholders and development teams to deliver solutions from concept through design, deployment, operations, and validation — all within a fast-paced, agile environment.
Responsibilities and Duties
- Design, build, and maintain robust, scalable, and efficient data pipelines and architectures.
- Implement complex transformations for large-scale structured and unstructured datasets.
- Develop and optimize ETL/ELT workflows using modern tools and orchestration frameworks.
- Ensure data quality, governance, security, and reliability across platforms.
- Prepare and deliver data structures that support predictive modeling, advanced analytics, and reporting.
- Implement monitoring, alerting, and performance optimization for data pipelines and platforms.
- Collaborate with product, engineering, and analytics teams to integrate and deploy data-driven solutions.
- Provide feedback and technical mentorship through peer code reviews and shared best practices.
- Contribute to architecture decisions for cloud-native, modern data warehouse environments.
Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related technical field.
- 5+ years of experience working with large-scale data systems, pipelines, and architectures.
- Advanced proficiency in SQL and data modeling for analytical and transactional workloads.
- Experience with PostGreSQL and MS SQL Server.
- Strong programming skills in Python, with experience in automating and optimizing data workflows.
- Hands-on experience with ETL/ELT frameworks and workflow orchestration tools (e.g., Airflow, dbt).
- Experience with modern cloud-based data warehouse platforms (Snowflake, Redshift).
- Experience with cloud platforms, preferably AWS, including storage, compute, and data services.
- Familiarity with DevOps practices, CI/CD pipelines, and containerization (Docker, Kubernetes, Terraform).
- Ability to leverage AI-assisted coding tools (e.g., GitHub Copilot, Claude, ChatGPT, or similar) to improve development efficiency and code quality.
- Strong analytical, problem-solving, and communication skills; ability to thrive in a fast-paced, collaborative environment.