Job Description

Job Purpose

We are seeking a highly skilled and Snowflake‑certified Data Engineer to independently design, build, and optimize scalable data solutions across the enterprise. The ideal candidate will have deep hands-on expertise in

Snowflake architecture, data modeling, and end‑to‑end pipeline development, along with a strong understanding of cloud data ecosystems, API integration, and enterprise data platforms. This individual contributor role requires a self-driven engineer capable of owning complex data engineering initiatives end‑to‑end while ensuring performance, reliability, and alignment with business needs.

Key Responsibilities

  • Independently design and implement Snowflake databases, schemas, warehouses, RBAC, and workload management.
  • Configure and optimize Snowpipe, Streams, Tasks, Materialized Views, Clustering, and Time Travel.
  • Perform performance tuning and troubleshoot issues directly from the Snowflake portal.
  • Design robust dimensional and normalized data models aligned with financial domain needs.
  • Architect and implement Medallion (Bronze–Silver–Gold) data layers for scalable pipelines.
  • Ensure data quality, governance, and secure access patterns.
  • Build and manage end-to-end pipelines using:
  • dbt for transformations
  • Python for automation
  • Airflow/ADF for orchestration
  • Implement and maintain CI/CD workflows, code reviews, and automated deployment processes.
  • Consume REST/SOAP APIs for data ingestion and integration.
  • Connect Snowflake with enterprise systems (Salesforce, SAP, CRM/ERP, cloud services).
  • Integrate Snowflake with cloud-native services for ingestion, compute, and storage.
  • Maintain high-performance, cost-efficient cloud data operations.
  • Take complete ownership of design, development, deployment, and support with minimal oversight.
  • Work directly with architects, business analysts, and stakeholders to translate requirements into solutions.
  • Produce high-quality documentation, reusable components, and engineering best practices.

Key competencies

  • Candidates should have a B.E./B.Tech/MCA/MBA in Information Systems, Computer Science or a related field
  • 10–12 years of hands-on data engineering experience, including a minimum of 6 years dedicated to Snowflake.
  • Advanced expertise in Snowflake architecture, implementation, administration, optimization, and troubleshooting.
  • Experience with Snowflake Data Sharing and Snowflake Marketplace for accessing, integrating, and managing third‑party and shared datasets.
  • Strong knowledge of data modeling and Medallion Architecture.
  • Proficiency in SQL, Python, and cloud ecosystem workflows.
  • Hands-on experience with dbt, Airflow, Azure Data Factory (ADF), or similar orchestration tools.
  • Experience integrating REST/SOAP APIs and connecting Snowflake with enterprise platforms (CRM/ERP/SaaS systems).
  • Strong exposure to Azure or AWS cloud data services.
  • Experience working in the financial domain (preferred but not mandatory).
  • Familiarity with CI/CD, Git workflows, automated deployments, and DevOps best practices.
  • Strong problem-solving skills, with ability to independently debug and resolve platform issues using Snowflake portal/console.
  • Excellent communication skills, self-driven attitude, and ability to work independently with minimal supervision.
  • Snowflake Certification (e.g., SnowPro Core or Advanced Data Engineer).


Job Details

Role Level: Not Applicable Work Type: Full-Time
Country: India City: Gurugram ,Haryana
Company Website: https://www.acuityanalytics.com/ Job Function: Data Science & AI
Company Industry/
Sector:
Banking And Real Estate

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About the Company

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