Data Engineer
New
W
Weekday AIData engineering
Location: India; Location: RemoteFull-TimeMiddle
Salary2,000,000 - 3,000,000 INR per year
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Job Details
- Experience
- 3+ years of professional experience building data pipelines and analytics platforms in a production environment.
- Required Skills
- PostgreSQLPythonSQLETLSnowflakeBigQueryLangChain
Requirements
- Have 3+ years of professional experience building data pipelines and analytics platforms in a production environment.
- Demonstrate strong Python programming skills and experience writing reusable, testable code.
- Have deep knowledge of SQL.
- Have experience with modern database systems such as PostgreSQL, BigQuery, or Snowflake.
- Have experience integrating PostHog for behavioral data ingestion and analysis.
- Have hands-on experience with deepeval or similar model evaluation frameworks.
- Be familiar with LangChain for LLM-driven data workflows and prompt engineering.
- Have experience with Streamlit or comparable open-source tools for interactive dashboards.
- Be able to collaborate with cross-functional teams in a remote, agile environment.
- Demonstrate problem-solving skills and the ability to troubleshoot complex data issues under tight deadlines.
- Be committed to code quality, documentation, and continuous learning.
Responsibilities
- Design and implement ETL pipelines to ingest, transform, and store data from diverse sources in a unified data warehouse.
- Build and maintain Streamlit dashboards and visualizations for product, marketing, and engineering teams.
- Integrate PostHog event data into the analytics pipeline and create segmented user funnels.
- Develop and maintain LangChain workflows for conversational AI features that interact with structured data.
- Use deepeval to automate machine learning model evaluation against business KPIs.
- Optimize SQL queries and database schemas for speed, reliability, and scalability.
- Provision and manage queryable data lakes and data marts in collaboration with data scientists.
- Implement data governance, security, and privacy controls to comply with industry regulations.
- Monitor pipeline health, troubleshoot failures, and improve performance.
- Document data architecture, pipeline logic, and best practices.
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