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Snap Analytics

Unifies data into AI-ready foundations

Data Platform Consultant

Data EngineeringUpdated on Nov 14
Full-timePune, Maharashtra, IndiaNo salary listed

About the Job

Requirements

  • At least 4 years of experience independently managing priorities and driving outcomes across projects.
  • Experience building data pipelines and data models using modern cloud data warehouses or data lakes, including Snowflake, Databricks, Matillion, and dbt.
  • Proficiency in PySpark and Fabric Data Factory or another ETL tool.
  • Experience building CI/CD pipelines using Bitbucket or GitHub.
  • Experience using AWS or equivalent cloud services, including SQS, SNS, cloud storage, and CloudWatch.
  • Strong SQL skills and at least 4 years of experience with ETL tools such as Fabric Data Factory and dbt.
  • Familiarity with cloud platforms such as Snowflake, Databricks, Redshift, BigQuery, or Synapse.
  • Ability to design and implement strategic technology solutions.
  • Consulting experience and the ability to interact with clients.
  • Ability to facilitate discussions with clients and adapt communication to different audiences.
  • Ability to offer multiple approaches to problems and balance trade-offs.
  • Ability to build consensus across stakeholders.
  • Experience mentoring others and contributing to internal improvements.

Responsibilities

  • Lead delivery of data solutions for clients, working with stakeholders to understand business needs and implement high-quality outcomes.
  • Build data pipelines and data models using modern cloud data warehouse and data lake technologies.
  • Facilitate client discussions and workshops to shape project direction.
  • Lead a small team to deliver a complex data solution.
  • Mentor junior colleagues and contribute to internal improvements.
  • Identify opportunities to add business value and strengthen client relationships.

About the Company

Snap Analytics

Unifies data into AI-ready foundations

Snap Analytics helps large organisations turn complex, fragmented data into AI-ready foundations by unifying, modernising and activating data. It focuses on enterprise data modernisation and end-to-end data-to-AI delivery, building a single trusted data foundation that powers real-time workflows, automation and measurable outcomes. Their approach spans defining the right platform and roadmap, engineering robust data foundations, and activating high-value AI use cases, with pre-built frameworks and deep real-world expertise. They work with SAP, Snowflake, and Databricks modernisation, data engineering, data science and AI operations, offering modular services or full-scale transformations so clients can move from data strategy to production-ready AI. The goal is to help organisations unlock data value and achieve a competitive advantage through practical, production-ready AI and data governance.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Bristol, United Kingdom
Founded
2012

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