๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ฎ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ฏ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ฎ๐ฌ-๐ฏ๐ฌ ๐๐ฃ๐)
Experience: 3+ yrs
Location: Remote
As a Data Engineer, you will design, build, and maintain scalable data pipelines and analytics platforms that drive business insights and product innovations. Leveraging your expertise in Python and SQL, you will transform raw data into clean, structured datasets, enabling data scientists and product teams to accelerate experimentation. You will integrate Posthog for behavioral analytics, employ deepeval for model validation workflows, and use Streamlit and LangChain to create interactive data tools and prompt-based applications. Your role will ensure data quality, performance, and compliance across the organization while collaborating closely with cross-functional stakeholders to translate data needs into technical solutions.
Requirements
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โข Design and implement robust ETL pipelines that ingest, transform, and store data from diverse sources into a unified data warehouse.
โข Build and maintain dashboards and data visualizations using Streamlit to provide realโtime insights for product, marketing, and engineering teams.
โข Integrate Posthog event data into the analytics pipeline and create segmented user funnels for product optimization.
โข Develop and maintain LangChain workflows to power conversational AI features that interact with structured data.
โข Employ deepeval to automate evaluation of machine learning models, ensuring model performance aligns with business KPIs.
โข Optimize SQL queries and database schemas for speed, reliability, and scalability across large datasets.
โข Collaborate with data scientists to provision and manage queryable data lakes and data marts.
โข Implement data governance, security, and privacy controls to comply with industry regulations.
โข Monitor pipeline health, troubleshoot failures, and iterate on performance enhancements.
โข Document data architecture, pipeline logic, and best practices for internal and external stakeholders.
๐ช๐ต๐ฎ๐ ๐ ๐ฎ๐ธ๐ฒ๐ ๐ฌ๐ผ๐ ๐ฎ ๐๐ฟ๐ฒ๐ฎ๐ ๐๐ถ๐
โข 3+ years of professional experience building data pipelines and analytics platforms in a production environment.
โข Strong programming skills in Python, with extensive experience in writing reusable, testable code.
โข Deep knowledge of SQL and experience with modern database systems such as PostgreSQL, BigQuery, or Snowflake.
โข Proven track record of integrating Posthog for behavioral data ingestion and analysis.
โข Handsโon experience with deepeval or similar model evaluation frameworks.
โข Familiarity with LangChain for building LLMโdriven data workflows and prompt engineering.
โข Solid understanding of Streamlit or comparable openโsource toolkits for building interactive dashboards.
โข Ability to collaborate effectively with crossโfunctional teams in a remote, agile environment.
โข Strong problemโsolving mindset, with the capacity to troubleshoot complex data issues under tight deadlines.
โข Commitment to code quality, documentation, and continuous learning in the fastโmoving data engineering landscape.