Assistant Manager - Data Engineer

Job Overview

Job Title: Sr. Azure Data Engineer Level:

Hiring Location: Bangalore / Chennai Department/Group: Technology

Business Unit: Digital Services CDO Travel Required: No

Salary Range: - Sub Process: Voice/Non-Voice: NA

Grade Reporting To: Data Engineering Lead

Key Skills and Responsibilities

We are seeking a Senior Data Engineer with a strong background in cloud-native data engineering, primarily on

Microsoft Azure, and familiarity with AWS and GCP. The ideal candidate will have deep expertise in building

scalable data pipelines, implementing enterprise-grade data governance, security, and AI-powered engineering

automation.

This role will play a pivotal part in designing, developing, and optimizing data ingestion, transformation, and

governance frameworks, enabling real-time and batch data analytics across our data platform.

Key Responsibilities:

Design and implement scalable, robust, and secure data pipelines using:

Azure Data Factory, Databricks, Synapse Analytics

Azure Data Lake Gen2, Event Hub, Azure Functions

Develop and maintain ETL/ELT processes for structured and unstructured data

Implement Change Data Capture (CDC), streaming pipelines, and batch ingestion

Work with AWS Glue, S3, Redshift or GCP BigQuery, Dataflow as needed

Optimize performance and cost across data workloads and cloud environments

Establish and maintain data quality frameworks, observability tools, and monitoring dashboards

Define and enforce data rules, validations, anomaly detection and reconciliation

Implement data lineage and metadata tracking using Azure Purview

Drive adoption of data cataloguing, profiling, and classification tools

Collaborate with data stewards and compliance teams to ensure governance alignment

Implement role-based access control (RBAC), data masking, encryption, and tokenization

Responsible for technical design, coding, unit testing, test case documentation, and walkthroughs

for all assigned Azure related projects to support company business and operational needs.

Ensures software developed follows the defined programming standards and follows the code /design review processes. Critically evaluate information gathered from multiple sources, reconcile conflicts, decompose high-level information into details, abstract up from low level information to a general understanding, and distinguish user requests from the underlying true needs. Collaborate with developers and subject matter experts to establish the technical vision and analyse trade-offs between usability and performance needs. Mentor junior data engineers and contribute to technical best practices

Qualification Experience Technical Skills: 4+ years in data engineering with at least 2+ years on Azure cloud platform Hands-on with Azure Data Factory, Azure Data Lake Gen2, Databricks, Synapse, Purview Proficiency in SQL, PySpark, Python, and data orchestration tools Strong understanding of data architecture patterns Lakehouse, medallion, delta architecture Familiarity with Snowflake, BigQuery, Redshift, or AWS Glue Experience with data versioning and GitOps for data Working knowledge of data observability, lineage, cataloguing, data quality Exposure to privacy-enhancing techniques, access control, security auditing Exposure to machine learning use cases in data engineering pipelines, data quality, anomaly detection, and schema change detection Exposure to GenAI or agentic AI to Automate data cataloguing and metadata enrichment etc. Experience with NLP or LLMs in metadata extraction or data classification is a plus Soft Skills: - Strong problem-solving, communication, and stakeholder collaboration skills Ability to lead data initiatives and mentor team members Proactive in learning and adopting emerging technologies in data AI Qualification: - Candidate must be BE/BTech/MCA with 4 to 8 years experience in Data Engineering.

Personal Attributes/Traits Consultative Socially confident Achievement oriented Decisive and action oriented Creative Eager to learn Resilient Competencies Business Foresight Influencing Others Fostering Partnerships With Customers Managing Transformation Driving Excellence Leading Teams Working Across Boundaries