Job Description

Roles & responsibilities

The Senior Associate 2 – Data Engineering Developer is a senior individual contributor responsible for designing, building, and optimizing scalable data pipelines, data models, and integration solutions. The role requires strong hands‑on expertise in modern data engineering tools and cloud platforms (Azure/AWS/GCP), along with the ability to work independently, collaborate with cross‑functional teams, and drive high‑quality data delivery.

Key Responsibilities:

Perform and oversee data transformation and integration projects using Azure Databricks, Azure Data Factory, and Python/PySpark.
Design and manage scalable data processing pipelines and workflows to support analytics and audit requirements.
Apply advanced concepts such as partitioning, optimization, and performance tuning for efficient data processing.
Integrate Databricks with ERP or third-party systems via APIs, developing robust business transformation logic.
Design, develop, and maintain robust ETL/ELT pipelines using modern data engineering tools.
Implement scalable data ingestion from structured and unstructured sources.
Ensure pipelines are optimized for performance, reliability, and reusability.
Develop automated data quality checks, validation frameworks, and monitoring solutions.
Develop end‑to‑end data workflows using cloud services (Azure Data Factory, Synapse, Databricks
Debug, optimize, and resolve issues in large-scale data workflows, proposing effective solutions with minimal guidance.
Foster a collaborative and inclusive team environment, promoting knowledge sharing and best practices.
Maintain accurate project status for self and team, ensuring timely delivery of milestones.
Coach junior team members and facilitate knowledge transfer for engagements of varying complexity.
Data Handling & Workflow Development
Demonstrate advanced knowledge of Azure cloud services, including Azure Databricks, Data Factory, Data Lake Storage, and related technologies.
Utilize tools such as Alteryx and PowerBI for data analysis and visualization.
Apply understanding of audit processes, financial data structures, and risk assessment routines.
Explore and apply Azure AI services to enhance business processes.

Performance Optimization & Debugging
Debug, optimize, and tune performance for large-scale data processing workflows.

Roles & responsibilities

The Senior Associate 2 – Data Engineering Developer is a senior individual contributor responsible for designing, building, and optimizing scalable data pipelines, data models, and integration solutions. The role requires strong hands‑on expertise in modern data engineering tools and cloud platforms (Azure/AWS/GCP), along with the ability to work independently, collaborate with cross‑functional teams, and drive high‑quality data delivery.

Key Responsibilities:

Perform and oversee data transformation and integration projects using Azure Databricks, Azure Data Factory, and Python/PySpark.
Design and manage scalable data processing pipelines and workflows to support analytics and audit requirements.
Apply advanced concepts such as partitioning, optimization, and performance tuning for efficient data processing.
Integrate Databricks with ERP or third-party systems via APIs, developing robust business transformation logic.
Design, develop, and maintain robust ETL/ELT pipelines using modern data engineering tools.
Implement scalable data ingestion from structured and unstructured sources.
Ensure pipelines are optimized for performance, reliability, and reusability.
Develop automated data quality checks, validation frameworks, and monitoring solutions.
Develop end‑to‑end data workflows using cloud services (Azure Data Factory, Synapse, Databricks
Debug, optimize, and resolve issues in large-scale data workflows, proposing effective solutions with minimal guidance.
Foster a collaborative and inclusive team environment, promoting knowledge sharing and best practices.
Maintain accurate project status for self and team, ensuring timely delivery of milestones.
Coach junior team members and facilitate knowledge transfer for engagements of varying complexity.
Data Handling & Workflow Development
Demonstrate advanced knowledge of Azure cloud services, including Azure Databricks, Data Factory, Data Lake Storage, and related technologies.
Utilize tools such as Alteryx and PowerBI for data analysis and visualization.
Apply understanding of audit processes, financial data structures, and risk assessment routines.
Explore and apply Azure AI services to enhance business processes.

Performance Optimization & Debugging
Debug, optimize, and tune performance for large-scale data processing workflows.

Mandatory technical & functional skills
Proficiency in Azure, DataBricks Notebooks, SQL, Python or Pyspark notebooks development.
Knowledge on any ERP and about the dataflows in ERP
Strong knowledge of ETL tools and processes.
Hands-on experience with Azure Databricks, Azure Data Factory (ADF), Azure Data Lake Storage (ADLS)
Comprehensive knowledge of Azure cloud services.
Experience with Databricks notebooks for building transformations and creating tables.

This role is for you if you have the below
Educational qualifications
B. Tech/B.E/MCA (Computer Science / Information Technology)

Work experience
Minimum 6–8 years of experience in data engineering, with deep expertise in Azure technologies.