Job Description
Key Responsibilities - Design, develop, and maintain scalable ETL pipelines and DataOps workflows - Build robust processes to integrate internal and external data sources with quality checks - Automate manual tasks and optimize data ingestion and delivery processes - Collaborate with cross-functional teams including product, marketing, and business development - Support technology teams in evaluating and setting up tools for data governance and analytics - Drive innovation in data infrastructure, quality, and reporting standards Requirements Experience & Education - Minimum 2 years of experience in data engineering - Open to candidates from any academic background with relevant experience Technical Expertise - Proficiency in building scalable data pipelines and warehouses - Experience with Python, Scala, PySpark, or PL/SQL - Hands-on experience with cloud platforms (e.g., AWS, S3, Redshift, Glue, etc.) - Familiarity with distributed systems (e.g., Hadoop, Spark), NoSQL databases, and cloud data warehouses (e.g., Snowflake, BigQuery) Personal Attributes - Strong problem-solving and analytical skills - Entrepreneurial mindset and initiative-driven - Excellent communication and collaboration skills - A team player who supports others and contributes positively to team culture Skills: Data Integration, Cloud Infrastructure, data engineering , pipeline development, Performance Optimization Experience: 0.00-4.00 Years
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