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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โขDesign and implement robust ETL pipelines that ingest, transform, and store data from diverse sources into a unified data warehouse.
โขBuild and maintain dashboards and data visualizations using Streamlit to provide realโtime insights for product, marketing, and engineering teams.
โขIntegrate Posthog event data into the analytics pipeline and create segmented user funnels for product optimization.
โขDevelop and maintain LangChain workflows to power conversational AI features that interact with structured data.
โขEmploy deepeval to automate evaluation of machine learning models, ensuring model performance aligns with business KPIs.
โขOptimize SQL queries and database schemas for speed, reliability, and scalability across large datasets.
โขCollaborate with data scientists to provision and manage queryable data lakes and data marts.
โขImplement data governance, security, and privacy controls to comply with industry regulations.
โขMonitor pipeline health, troubleshoot failures, and iterate on performance enhancements.
โขDocument data architecture, pipeline logic, and best practices for internal and external stakeholders.
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โข3+ years of professional experience building data pipelines and analytics platforms in a production environment.
โขStrong programming skills in Python, with extensive experience in writing reusable, testable code.
โขDeep knowledge of SQL and experience with modern database systems such as PostgreSQL, BigQuery, or Snowflake.
โขProven track record of integrating Posthog for behavioral data ingestion and analysis.
โขHandsโon experience with deepeval or similar model evaluation frameworks.
โขFamiliarity with LangChain for building LLMโdriven data workflows and prompt engineering.
โขSolid understanding of Streamlit or comparable openโsource toolkits for building interactive dashboards.
โขAbility to collaborate effectively with crossโfunctional teams in a remote, agile environment.
โขStrong problemโsolving mindset, with the capacity to troubleshoot complex data issues under tight deadlines.
โขCommitment to code quality, documentation, and continuous learning in the fastโmoving data engineering landscape.