Senior Data Engineer / Analytics Engineer (India-Based)

Job Description

Mercor is partnering with a cutting-edge AI research lab to hire a **Senior Data/Analytics Engineer** with expertise across **DBT** and **Snowflake’s Cortex CLI**. In this role, you will build and scale Snowflake-native data and ML pipelines, leveraging Cortex’s emerging AI/ML capabilities while maintaining production-grade DBT transformations. You will work closely with data engineering, analytics, and ML teams to prototype, operationalise, and optimise AI-driven workflows—defining best practices for Snowflake-native feature engineering and model lifecycle management.
This is a high-impact role within a modern, fully cloud-native data stack.
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## **Responsibilities**

– Design, build, and maintain **DBT models, macros, and tests** following modular data modeling and semantic best practices.

– Integrate **DBT workflows with Snowflake Cortex CLI**, enabling:

– Feature engineering pipelines

– Model training & inference tasks

– Automated pipeline orchestration

– Monitoring and evaluation of Cortex-driven ML models

– Establish best practices for **DBT–Cortex architecture and usage patterns**.

– Collaborate with data scientists and ML engineers to **produce Cortex workloads** in Snowflake.

– Build and optimise **CI/CD pipelines** for dbt (GitHub Actions, GitLab, Azure DevOps).

– Tune Snowflake compute and queries for **performance and cost efficiency**.

– Troubleshoot issues across DBT arti-facts, Snowflake objects, lineage, and data quality.

– Provide guidance on **DBT project governance, structure, documentation, and testing frameworks**.
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## **Required Qualifications**

– **3+ years** experience with **DBT Core or DBT Cloud**, including macros, packages, testing, and deployments.

– Strong expertise with **Snowflake** (warehouses, tasks, streams, materialised views, performance tuning).

– Hands-on experience with **Snowflake Cortex CLI**, or strong ability to learn it quickly.

– Strong SQL skills; working familiarity with **Python** for scripting and DBT automation.

– Experience integrating DBT with orchestration tools (Airflow, Dagster, Prefect, etc.).

– Solid understanding of **modern data engineering, ELT patterns, and version-controlled analytics development**.
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## **Nice-to-Have Skills**

– Prior experience operationalising **ML workflows inside Snowflake**.

– Familiarity with **Snow-park**, Python UDFs/UDTFs.

– Experience building **semantic layers** using DBT metrics.

– Knowledge of **MLOps / DataOps** best practices.

– Exposure to **LLM workflows, vector search, and unstructured data pipelines**.
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## **Why Join**

– You will be an **hourly contractor through Mercor**, working **20–40 hours per week** with flexibility.

– Direct opportunity to build **next-generation Snowflake AI/ML systems** with Cortex.

– High-impact ownership of DBT and Snowflake architecture across production pipelines.

– Work alongside top-tier ML engineers, data scientists, and research teams.

– Fully remote, high-autonomy environment focused on innovation, velocity, and engineering excellence.