Data Engineer

Job Description We are looking for a skilled Data Engineer with 3+ years of experience to design, build, and maintain scalable data pipelines and data platforms. The ideal candidate will work closely with data scientists, analysts, and business stakeholders to ensure high-quality, reliable, and performant data solutions. Key Responsibilities Design, develop, and maintain end-to-end ETL/ELT data pipelines Build and optimize data ingestion frameworks from multiple sources (APIs, databases, files, streaming Work with data warehouses and lakehouse architectures (Snowflake, Redshift, BigQuery, Databricks, etc.) Develop and maintain batch and near-real-time pipelines Ensure data quality, validation, monitoring, and observability Optimize SQL queries and data models for performance and scalability Collaborate with analytics, BI, and ML teams to support reporting and advanced analytics Implement data governance, security, and access controls Automate workflows using orchestration tools (Airflow, Luigi, etc.) Troubleshoot and resolve data pipeline and production issues Required Skills & Qualifications Must-Have 3+ years of hands-on experience as a Data Engineer Strong proficiency in Python and SQL Experience with ETL/ELT pipeline development Hands-on experience with data warehouses (Snowflake preferred) Experience with Apache Airflow or similar orchestration tools Strong understanding of data modeling (star/snowflake schemas) Experience working with large-scale datasets Familiarity with Git-based version control Experience working in agile environments Good to Have Experience with Apache Spark / PySpark Exposure to Kafka or streaming platforms Knowledge of cloud platforms (AWS / Azure / GCP) Experience with Docker & Kubernetes Familiarity with data quality frameworks (Great Expectations, Soda, etc.) BI tools experience (Power BI, Looker, Tableau) Infrastructure-as-Code tools (Terraform, CloudFormation) CI/CD pipelines for data workflows