DATA ENGINEER

This is a remote position. The Data Engineer will be responsible for building reliable data pipelines, integrating multiple data sources, and ensuring high-quality, accessible, and well-structured data for analytics and product teams. The role works closely with Product, Analytics, Engineering, and Cloud teams to enable data-driven decision-making. Key Responsibilities Design, build, and maintain scalable data pipelines and ETL/ELT processes. Integrate data from multiple sources, including APIs, databases, and third-party systems. Develop and optimize data models for analytics and reporting use cases. Ensure data quality, integrity, and consistency across systems. Support real-time and batch data processing workflows. Collaborate with Product and Analytics teams to define data requirements. Monitor and troubleshoot data pipeline performance and failures. Implement data governance, security, and access controls. Support BI and analytics teams with clean and structured datasets. Continuously improve data architecture, performance, and scalability. Required Qualifications 6-8 years of experience in data engineering or related roles. Strong understanding of data structures, databases, and data modeling. Experience building ETL/ELT pipelines in production environments. Good problem-solving and analytical skills. Experience working in Agile and cross-functional teams. Strong communication and documentation abilities. Technical Skills Programming: Python, SQL (advanced level) Data Processing: Spark, Kafka, or similar distributed systems (preferred) Databases: PostgreSQL, MySQL, MongoDB, or equivalent Data Warehousing: Snowflake, BigQuery, Redshift (preferred) Cloud Platforms: Amazon Web Services / Azure / GCP ETL/ELT Tools: Airflow, dbt, or similar Version Control: Git / GitHub / GitLab BI Tools: Tableau, Power BI, or similar (supporting role) Tableau Originally posted on Himalayas