Data Engineer

Design and maintain scalable data pipelines and infrastructure that support analytics, AI initiatives, and enterprise data driven solutions across cloud and on premise environments. Key Responsibilities: Build and maintain scalable ETL/ELT pipelines and distributed data processing workflows Manage data warehouses, data lakes, and streaming platforms while ensuring performance, scalability, and reliability Integrate and transform data from APIs, databases, flat files, and real-time streaming sources Implement data governance, validation, monitoring, and security best practices across the data ecosystem Collaborate with data scientists, ML engineers, and business teams to deliver reliable and accessible datasets

Desired Candidate Profile

• Minimum 5 years of experience in data engineering or large-scale backend data systems
• Strong experience with Apache Spark, Hadoop, Flink, SQL/NoSQL databases, and data warehousing solutions such as Snowflake or BigQuery
• Proficiency in Python, SQL, Bash scripting, ETL/ELT development, and API-based integrations
• Familiarity with Kafka, Kinesis, CI/CD pipelines, and DevOps practices
• Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or a related field
• Strong analytical thinking and troubleshooting capabilities
• Excellent communication and collaboration skills
• High attention to detail with a strong quality mindset
• Ability to work effectively in fast-paced and cross-functional environments
• Strong ownership, reliability, and continuous improvement mindset