Senior/Data Engineer
Summary
Build and maintain scalable ETL/ELT pipelines and data warehouses using Python, SQL, and cloud platforms to power analytics and AI products.
Job Description
The Data Engineer is responsible for building and maintaining the data infrastructure that powers analytics, reporting, and AI products. You will design scalable ETL/ELT pipelines, manage data warehouses, and ensure data is accurate, reliable, and accessible to stakeholders. You will work cross‑functionally with Data Scientists, Analysts, and Product teams to translate business requirements into robust data solutions. This role is hands‑on and requires strong skills in SQL, Python, and cloud data platforms, with a focus on automation, performance, and data quality.
Responsibilities
- Design, develop, and optimize scalable ETL/ELT pipelines to ingest data from databases, APIs, SaaS platforms, and flat files.
- Build and maintain data warehouses, data marts, and semantic layers to support reporting and analytics.
- Implement data validation, lineage tracking, and quality checks to ensure accuracy and reliability.
- Deploy and manage data workflows using orchestration tools like Airflow; automate ingestion, transformation, and loading.
- Optimize SQL queries, pipeline runtime, and storage for cost and speed.
- Work with stakeholders to translate business requirements into technical data solutions.
- Maintain clear documentation of data flows, schemas, and processes.
Requirements
- At least 2–4 years in data engineering, backend engineering, or similar.
- Hands‑on with ETL/ELT tools such as Apache Airflow, Talend, Informatica, Fivetran, or dbt.
- Strong proficiency in Python and SQL; experience with PySpark is a plus.
- Experience with relational databases like PostgreSQL, MySQL, SQL Server and data warehouses such as Snowflake, BigQuery, or Redshift (preferred).
- Hands‑on experience with AWS data services (S3, Glue, EMR, Redshift, Lambda).
- Experience with GCP (BigQuery, Dataflow, Cloud Composer) is a plus.
- Familiarity with Git, CI/CD, Docker, and data modeling concepts.
- Strong problem‑solving, attention to detail, and ability to work in a fast‑paced environment.
- Experience with streaming data tools like Kafka, Spark Streaming is a good to have.
- Knowledge of data governance, security, and compliance best practices is a good to have.
- Experience supporting analytics and ML/AI use cases is a good to have.
- This role will need to secure a clearance due to the sensitivity of the project.
How to Apply
Please send your latest CV in MS Word format to jennifer@zenithinfotech.com.sg.