Data Engineer

• Design and build scalable ETL/ELT pipelines for batch and real-time data processing.
• Develop and maintain data ingestion frameworks from multiple sources (APIs, databases, logs, events).
• Ensure data quality, consistency, and reliability across systems.
• Build and manage data warehouses and data lakes.
• Optimise data models for analytics, reporting, and downstream consumption.
• Implement data partitioning, indexing, and performance tuning strategies.
• Work closely with Data Analysts, Data Scientists, and Backend Engineers.
• Translate business requirements into efficient data solutions.
• Support analytics and ML workflows with clean, well-structured datasets.
• Set up monitoring, alerting, and logging for data pipelines.
• Troubleshoot and resolve data issues and failures.
• Ensure security, governance, and compliance best practices.

Requirements:

• Strong programming skills in Python / Scala / Java / SQL.
• Experience with ETL tools and frameworks (Airflow, dbt, Spark, Flink, Kafka).
• Solid understanding of data warehousing concepts (Snowflake, BigQuery, Redshift).
• Hands-on experience with cloud platforms (AWS / GCP / Azure).
• Experience with relational and NoSQL databases.
• Strong SQL skills for data transformation and analysis.
• Knowledge of data modelling (star/snowflake schema).
• Understanding of stream processing and event-driven architectures.
• Experience working with large-scale, distributed data systems.
• Experience supporting ML pipelines and feature stores.
• Knowledge of data governance, lineage, and metadata management.
• Exposure to real-time analytics and streaming platforms.
• Experience in SaaS or product-based companies.