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