Production Support Data EngineerStraight from Algoworks’s careers page. Apply on the company site — no recruiter, no middleman.
Production Support Data Engineer
Location: Noida, India
Department: PE-Cloud
Experience: 7+
Skills: ADLS Gen2, Azure Data Factory, PySpark, Databricks
Role: Azure Data Engineer
Location: Remote, India
Experience: 7+ Years
Algoworks
About the Company
Algoworks is an award-winning artificial intelligence, engineering services and experience transformation firm with offices across the United States, Europe, South America and India. We bring together a global team of engineers, architects, designers, researchers and operators united by rigor, accountability and a commitment to delivering measurable results.
For over 20 years, Algoworks has partnered with Fortune 500 organizations across the Americas, Europe and Asia to define, build and run technology that drives meaningful business outcomes. Our work combines human-centered design, engineering excellence and AI-powered capabilities to solve complex challenges with clarity and precision. Innovation, particularly in the responsible application of AI, is embedded in how teams approach problem-solving and continuous improvement.
At Algoworks, growth is continuous and closely tied to impact. Teams collaborate across geographies and disciplines, strengthening outcomes through shared insight and collective expertise. The culture values transparency, open dialogue and an environment where every voice is heard and contribution is recognized.
Through collaboration, accountability and a focus on results, Algoworks operates at the intersection of technology and people, building not only advanced systems but strong global teams that elevate performance and create lasting impact.
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Role Overview
We are looking for an experienced Azure Data Engineer with strong hands-on expertise in Azure Databricks, PySpark, SQL, Delta Lake, and Medallion Architecture. This role primarily focuses on production support, code migration, and implementation of released changes within an existing enterprise data platform.
The ideal candidate will be comfortable working with Git repositories, identifying ticket-specific code changes, safely integrating approved updates, troubleshooting production issues, and coordinating with client teams throughout migration and release activities.
Key Responsibilities
1. Production Support & Troubleshooting
- Work closely with client and development teams to understand production issues, change requests, and released tickets.
- Troubleshoot production pipeline failures, data issues, and transformation errors.
- Perform data validation, reconciliation, and root cause analysis.
- Investigate issues across existing enterprise data platforms and implement approved fixes.
- Coordinate with client teams to ensure timely resolution of production issues.
2. Git Management & Code Migration
- Review Git repositories and identify code changes associated with released tickets.
- Perform Git cherry-picking, branch management, merge conflict resolution, and code integration.
- Apply approved changes to existing Databricks notebooks, PySpark code, SQL transformations, and data pipelines.
- Ensure code changes are integrated safely into existing codebases.
- Support migration of changes across Development, UAT, and Production environments.
3. Azure Databricks & Data Engineering
- Support and maintain data pipelines using Azure Databricks, PySpark, Azure Data Factory, and ADLS Gen2.
- Apply changes to existing notebooks, data transformations, and processing workflows.
- Work with Delta Lake and Delta Tables, including MERGE operations, incremental processing, schema evolution, Change Data Feed (CDF), and optimization.
- Maintain data quality and consistency across processing stages.
- Work with Medallion Architecture to support structured data processing and transformation.
4. Release Management & Deployment Support
- Support the migration and implementation of approved changes across Dev, UAT, and Production environments.
- Coordinate with client teams during releases and production deployments.
- Validate deployed changes and investigate post-release issues.
- Follow established code integration, migration, and deployment procedures.
- Help maintain the reliability and stability of the existing enterprise data platform.
Required Technical Skills & Competencies
- Strong hands-on experience with Azure Databricks and PySpark.
- Strong SQL and data transformation skills.
- Experience with Delta Lake and Delta Tables.
- Good understanding of Medallion Architecture.
- Experience with Azure Data Factory and ADLS Gen2.
- Strong Git experience, particularly cherry-picking, branching, merging, and conflict resolution.
- Production support and troubleshooting experience.
- Experience working with existing enterprise data platforms and code migration activities.
- Ability to investigate data issues, perform reconciliation, and conduct root cause analysis.
- Experience implementing released changes and supporting deployments across multiple environments.
Must-Have Skills
- Azure Databricks
- PySpark
- SQL and Data Transformations
- Delta Lake / Delta Tables
- Medallion Architecture
- Azure Data Factory
- ADLS Gen2
- Git Cherry-Picking
- Branch Management and Merge Conflict Resolution
- Production Support and Troubleshooting
- Code Migration and Integration
- Data Validation and Reconciliation
- Dev, UAT, and Production Release Support
Good to Have Skills
- Azure Event Hubs
- Change Data Capture (CDC)
- Debezium
- Databricks Workflows and Jobs
- Unity Catalog
- Azure DevOps and CI/CD
- Experience with large-scale data platforms
- Data pipeline and performance optimization
Desired Attributes
- Hands-on approach to production support and data engineering.
- Strong troubleshooting and problem-solving skills.
- Ability to quickly understand existing codebases and identify ticket-specific changes.
- Careful and systematic approach to cherry-picking, code integration, and migration.
- Strong understanding of data quality and transformation logic.
- Ability to coordinate effectively with client and development teams.
- Strong ownership of release activities and production stability.
- Attention to detail when implementing changes across environments.
Interview Process
2–3 rounds of discussion.
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