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