Data Engineer

Location:
Vadodara

Department:
Data Engineering

Job Summary

We are seeking a versatile
Data, Analytics & MLOps Engineer
to join our growing AI Engineering team. The ideal candidate is an expert in designing robust data pipelines (ETL pipeline), managing data lakes (Data lake Architect), building enterprise-grade dashboards, and enabling automation and AI/ML workflows using modern DevOps and orchestration tools. You will contribute to a
unified data ecosystem
that supports advanced analytics, Data quality frameworks, reporting, and AI adoption at scale.

Key Responsibilities

Functional Area

Responsibilities

Data Engineering

• Design, develop, and maintain scalable data pipelines for ingestion, transformation, and quality. - Manage structured and unstructured data in Data Lakes (Azure, AWS S3, GCP).

ETL/ELT Orchestration

• Build ELT pipelines using
  Fivetran
  ,
  dbt
  ,
  Azure Data Factory
  ,
  Apache Airflow
  ,
  SSIS
  ,
  Talend
  .

Automation & Workflow

• Implement and maintain automation using
  Power Automate
  ,
  Pipefy
  , or
  Salesforce Workflows
  .

Dashboards & BI

• Develop analytics dashboards using
  Power BI
  ,
  Tableau
  ,
  Looker
  , or
  QlikView
  with data modeling and KPI visualizations.

Data Governance

• Implement data access, lineage, audit trails, and classification policies using tools like
  Purview
  ,
  Collibra
  , or
  Alation
  .

MLOps Engineering

• Operationalize ML pipelines using
  MLflow
  ,
  Azure ML
  ,
  Kubeflow
  ,
  SageMaker Pipelines
  . - Package and deploy models via CI/CD pipelines.

DevOps & CI/CD

• Integrate data and ML workflows with
  Azure DevOps
  ,
  GitHub Actions
  , or
  GitLab CI/CD
  .

Collaboration

• Partner with data scientists, product teams, and business stakeholders to deliver insight-driven solutions.

Required Skills & Experience

• 2–8 years of experience in
  Data Engineering
  ,
  Analytics
  , or
  MLOps
  roles.
• Strong programming skills in
  SQL
  ,
  Python
  , and optionally
  Scala
  or
  R
  .
• Experience with
  Cloud platforms
  :
  Azure
  (Data Lake Gen2, Synapse, Fabric),
  AWS
  (Glue, S3, Redshift),
  GCP
  (BigQuery, Dataflow).
• Hands-on with pipeline tools:
  Fivetran
  ,
  dbt
  ,
  ADF
  ,
  Apache Nifi
  ,
  Kafka
  .
• Visualization expertise in
  Power BI
  ,
  Looker
  ,
  Tableau
  , or similar.
• Experience with
  Power Automate
  ,
  Pipefy
  , or
  Salesforce Flow
  to automate business processes.
• Understanding of
  data warehouse
  concepts and dimensional modeling.
• Working knowledge of
  DataOps
  ,
  MLOps
  ,
  DevOps
  , and related best practices.

Desirable Skills

• Experience in
  event-driven architectures
  using
  Apache Kafka
  ,
  Event Hub
  , or
  Pub/Sub
  .
• Familiarity with
  GenAI pipelines
  ,
  RAG architecture
  , and
  vector databases
  like
  Pinecone
  ,
  Weaviate
  , or
  Qdrant
  .
• Exposure to
  Data Mesh
  ,
  Data Fabric
  , or
  Modern Data Stack
  .
• Experience in
  Salesforce Data Integration
  ,
  Power Platform
  , or
  Microsoft Fabric
  .
• Hands-on with
  PowerShell scripting
  or
  Bash
  for automation.

Certifications Preferred

• Microsoft Certified: Azure Data Engineer Associate / Azure AI Engineer Associate
• AWS Certified Big Data or Machine Learning
• GCP Professional Data Engineer
• dbt Fundamentals / Power BI Data Analyst Associate

Soft Skills

• Ownership mindset and ability to work in a fast-paced, ambiguous environment.
• Strong verbal and written communication for stakeholder alignment.
• Problem-solving skills with a business-outcome-driven mindset.

Opportunities

• Drive enterprise transformation through modern data and AI platforms.
• Work cross-functionally across
  supply chain
  ,
  customer insights
  ,
  marketing analytics
  , and
  finance intelligence
  .
• Engage in real-world
  GenAI readiness
  ,
  Copilot integration
  , and
  agentic AI
  deployments.