Data Engineer

Data Pipeline Development:Design, build, and maintain scalable and robust data pipelines (ETL/ELT) to ingest, clean, and transform data from multiple sources.

Data Integration & Architecture:Manage multi-database synchronization strategies, data migrations, and contribute to the structuring of data warehouses or data lakes.

Data Quality & Reliability:Ensure data integrity, availability, and security across the data infrastructure. Debug scripts, resolve data conflicts, and troubleshoot pipeline failures.

Infrastructure Monitoring:Utilize the ELK stack (Elasticsearch, Logstash, Kibana) or similar tools for log and event data management to monitor pipeline health and performance.

Cross-Functional Collaboration:Work closely with software developers, analysts, and Business Intelligence teams to provide reliable, optimized data that drives strategic business decisions.

Requirements:

Data Engineering & ETL Savvy:Proven experience building data pipelines and working with orchestration/ETL tools (e.g., Apache Airflow, SSIS, Informatica).

Expert in SQL & Programming:Extensive experience with complex SQL queries and relational database design. Strong proficiency in programming languages commonly used in data engineering (Python or Golang).

Hands-On Database

Experience:

Solid experience working with relational databases such as PostgreSQL, MySQL, and MSSQL Server.

Experience with Data Warehouse architecture is highly preferred. Proven experience in designing or building a
Data Lakehouse is a strong plus.

Streaming & Event Processing:Familiarity with message brokers and streaming platforms like Apache Kafka.

Cloud & Monitoring Tools:Knowledge of the ELK stack. Experience with DBaaS (Database as a Service) on Cloud platforms (AWS, GCP, or Azure) is a strong plus.

Work Arrangement:Willing to Work From Office (WFO - BSD CITY).

How many years' experience do you have as a Data Engineer?