Key Responsibilities: /n Pipeline development — Design, build, and maintain robust data pipelines to ingest new datasets onto the firm's data platform as demand arises from the investment and analyst teams. Automation — Automate ingestion, transformation, and data-quality workflows to reduce manual effort and speed up onboarding of current sources. /n Data platform — Structure and organize datasets so they can be integrated, joined, and queried effectively across the platform. /n /n
AI enablement (roadmap) — Process large volumes of documents into formats suitable for AI consumption; store and index content in vector databases; support retrieval workflows (RAG) that surface the right information reliably.

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Insight & reporting (roadmap) — Enable effective querying across multiple integrated datasets to combine information and support sensible, decision-ready reporting.

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Stakeholder collaboration — Work directly with the hiring manager and analysts to scope new requirements, prioritise the pipeline backlog, and respond quickly as new needs emerge.

/n /n Key Competencies: /n Required Skills • 4–5+ years of hands-on data engineering experience,



ideally within financial services or data intensive settings. /n /n
Strong experience building and orchestrating data pipelines with Apache Airflow.

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Solid working knowledge of Apache Spark for large-scale data processing.

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Solid Python and SQL skills, with a focus on clean, maintainable, production-quality code.

Experience designing data models and organizing datasets for downstream integration and querying.

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Track record of automating data workflows and building for reliability, monitoring, and data quality.

/n /n Nice to Have. /n /n
Exposure to AI/LLM engineering: document processing at scale, embeddings, and vector databases (e.g. pgvector, Pinecone, Weaviate, or similar).

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Experience building or supporting retrieval-augmented generation (RAG) workflows.

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Familiarity with cloud data platforms and modern data stack tooling.

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Prior experience supporting investment management, hedge fund, or capital markets data environments.

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Experience working as a dedicated remote resource embedded with a client team

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📌 Technical Lead Pune
🏢 Acuity Analytics
📍 Pune