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Circle K
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Lead Data Engineer

Lead Data Engineer

Circle K

8 - 10 years

10 - 12 Lacs

kolkata mumbai new delhi hyderabad pune chennai bengaluru

Posted:1 day ago| Platform:

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Skills Required

metadata version control mysql data quality unix shell scripting monitoring sql python auditing

Work Mode

Work from Office

Job Type

Full Time

Job Description

At Circle K, we are building a best-in-class global data engineering practice to support intelligent business decision-making and drive value across our retail ecosystem. As we scale our engineering capabilities, we re seeking a Lead Data Engineer to serve as both a technical leader and people coach for our India-based Data Enablement pod.

This role will oversee the design, delivery, and maintenance of critical cross-functional datasets and reusable data assets while also managing a group of talented engineers in India. This position plays a dual role: contributing hands-on to engineering execution while mentoring and developing engineers in their technical careers.

About the role

The ideal candidate combines deep technical acumen, stakeholder awareness, and a people-first leadership mindset. You ll collaborate with global tech leads, managers, platform teams, and business analysts to build trusted, performant data pipelines that serve use cases beyond traditional data domains.

Responsibilities

Design, develop, and maintain scalable pipelines across ADF, Databricks, Snowflake, and related platforms
Lead the technical execution of non-domain specific initiatives (e.g. reusable dimensions, TLOG standardization, enablement pipelines)
Architect data models and re-usable layers consumed by multiple downstream pods
Guide platform-wide patterns like parameterization, CI/CD pipelines, pipeline recovery, and auditability frameworks
Mentoring and coaching team
Partner with product and platform leaders to ensure engineering consistency and delivery excellence
Act as an L3 escalation point for operational data issues impacting foundational pipelines
Own engineering best practices, sprint planning, and quality across the Enablement pod
Contribute to platform discussions and architectural decisions across regions

Education

Bachelor s or master s degree in computer science, Engineering, or related field

Relevant Experience

8-10 years of data engineering experience with strong hands-on delivery using ADF, SQL, Python, Databricks, and Spark
Experience designing data pipelines, warehouse models, and processing frameworks using Snowflake or Azure Synapse

Knowledge and Preferred Skills

Proficient with CI/CD tools (Azure DevOps, GitHub) and observability practices.
Solid grasp of data governance, metadata tagging, and role-based access control.
Proven ability to mentor and grow engineers in a matrixed or global environment.
Strong verbal and written communication skills, with the ability to operate cross-functionally.
Certifications in Azure, Databricks, or Snowflake are a plus.
Strong Knowledge of Data Engineering concepts (Data pipelines creation, Data Warehousing, Data Marts/Cubes, Data Reconciliation and Audit, Data Management).
Working Knowledge of Dev-Ops processes (CI/CD), Git/Jenkins version control tool, Master Data Management (MDM) and Data Quality tools.
Strong Experience in ETL/ELT development, QA and operation/support process (RCA of production issues, Code/Data Fix Strategy, Monitoring and maintenance).
Hands on experience in Databases like (Azure SQL DB, Snowflake, MySQL/, Cosmos DB etc.), File system (Blob Storage), Python/Unix shell Scripting.
ADF, Databricks and Azure certification is a plus.

Technologies we use : Databricks, Azure SQL DW/Synapse, Snowflake, Azure Tabular, Azure Data Factory, Azure Functions, Azure Containers, Docker, DevOps, Python, PySpark, Scripting (Powershell, Bash), Git, Terraform, Power BI

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Lead Data Engineer