Lead Data Engineer

Zenith Infotech (S) Pte Ltd. was started in 1997, primarily with the vision of offering state-of-the-art IT Professionals and solutions to various organizations and thereby helping them increase their productivity and competitiveness. From deployment of one person to formation of whole IT teams, Zenith Infotech has helped clients with their staff augmentation needs. Zenith offers opportunity to be engaged in long term projects with large IT savvy companies, Consulting organizations, System Integrators, Government, and MNCs.

EA Licence No: 20S0237

Job:

• Own the design, development, and scaling of our data platform and pipelines.

• Lead a small team of data engineers, work closely with Data Science, Analytics, and Product, and ensure our data is reliable, scalable, and accessible for decision-making and ML products.

• Be hands-on with architecture and coding, while also mentoring engineers and setting engineering standards.

Role:

• Design and implement scalable, reliable, and cost-effective data pipelines and data platforms.

• Build and maintain ETL/ELT pipelines, data models, and APIs using Python, SQL, and modern cloud tools.

• Own data ingestion, storage, transformation, orchestration, and monitoring in cloud environments.

• Guide engineers, conduct code reviews, and drive best practices in data engineering.

• Partner with Data Science, Analytics, Product, and Business teams to translate requirements into technical solutions.

• Drive end-to-end delivery of data projects from requirements gathering to production deployment and support.

• Implement testing, monitoring, and data quality frameworks.

• Enforce data security, privacy, and compliance standards.

• Optimize pipeline performance, cost, and reliability.

• Troubleshoot production issues.

Requirements:

• Masters or Degree in Computer Science, Engineering, Mathematics, or related field.

• Equivalent practical experience will be considered.

• Has at least 6+ years in data engineering, with 2+ years in a lead/senior role.

• Strong in Python and SQL. Experience with PySpark is a plus.

• Hands-on experience with AWS, GCP, or Azure. Services like S3/ADLS, BigQuery/Redshift/Snowflake, Airflow, Kafka, DBT.

• Strong experience with dimensional modeling, data warehousing, and lakehouse architectures.

• Experience with Airflow, Prefect, or similar workflow tools

• Engineering practices: CI/CD, Docker, Git, Infrastructure as Code, unit testing.

• Good to Have: Kafka, Spark Streaming, Flink; Databases: PostgreSQL, MongoDB, Redis.

• Working with feature stores and model deployment pipelines.

• Experience hiring, mentoring, and doing technical interviews.

• Can explain complex technical concepts to non-technical stakeholders.

• Proactive problem solver who takes end-to-end ownership.

• Works well across Data Science, Analytics, and Engineering teams.

• The role will need to secure a clearance, due to the sensitivity of the project.

To apply:

Please send your latest CV in MS Word format to [email protected]

Appreciate the interest of all applicants; however only shortlisted candidates will be notified.