Lead Data Engineer

Job Description

Job Summary -

A mid-senior level Data Analyst lead to manage a critical project for one of our biggest client in insurance domain. The Individual should be passionate about technology, experienced in developing and managing cutting edge technology applications.

We are seeking an experienced Project Lead - Data Engineer to oversee the application support and maintenance of enterprise data pipelines and reporting systems. The ideal candidate will be responsible for ensuring seamless data operations, monitoring production pipelines, managing incidents and problems, conducting root cause analysis (RCA), and driving continuous improvements across the data ecosystem. This role also includes transitioning projects into support, mentoring a high-performing team, and delivering timely status updates to stakeholders.

Years of experience needed -

4 to 6 yrs

Technical / Non-Technical Skills

• Expert knowledge on Data profiling and SQL skills (Profiling, TSQL), Visualization skills (Power BI) and .net.
• Detail Knowledge on Coding & testing of required Data layer validations
• Should have exposure in estimation techniques and requirements gathering
• Hands on experience in Data Analyst/Data Engineer role
• Minimum of 4 to 6 years of IT experience in Data profiling and SQL skills (Profiling, TSQL), Visualization skills (Power BI) and .net.
• Microsoft Azure - With Data Lake and SQL Server Tech Stack
• Pipeline built and integrated using ADF for Orchestration and Data Lake from Storage
• PySpark
• ADLS Gen 2
• Data Vault leveraging Delta Lake
• Power BI for visualization
• Tools & Language:
• Azure Data Factory, Azure Data Lake Gen2, Databricks, Python
• Nice to have - Exposure to Jira and ServiceNow
  
  

Process Skills

• Capable of analyzing requirements and develop software as per project defined software process
• Develop and peer review of LLD (Initiate/ participate in peer reviews)
• Ability to execute test plans, create test cases test data and contribute to appropriate software (including programming languages) development life cycle methodology and application of specialized business and technical knowledge.
• Pipeline Monitoring & Maintenance: Oversee and proactively monitor data pipelines (batch and streaming) built on Azure Data Factory (ADF), PySpark, and Databricks, ensuring high availability and performance.
• Incident & Problem Management: Lead the end-to-end resolution of production issues, including triaging, resolution, and stakeholder communication. Maintain SLAs and ensure timely escalation when needed.
• Root Cause Analysis (RCA): Conduct in-depth RCA for recurring and critical issues, implement long-term solutions, and drive preventive measures to reduce incident frequency.
• Project Transition: Collaborate with development teams to ensure smooth handover of new projects and enhancements into support. Define support readiness criteria and lead knowledge transfer sessions.
• Team Leadership & Mentoring: Manage a support team by providing technical guidance, mentoring junior engineers, allocating tasks, and ensuring timely resolution of support tickets.
• Reporting & Communication: Prepare and present daily and monthly status reports, including SLA adherence, open incidents, problem records, trends, and improvement plans.
• Stakeholder Engagement: Work closely with data engineering, business intelligence, and product teams to resolve issues and align support with business priorities.
• BI Reports Support: Ensure business-critical BI reports are up-to-date and accurate, working with reporting tools and resolving issues related to data freshness and visualization.
  
  

Behavioral Skills

• Resolve technical issues of projects and Explore alternate designs
• Participates as a team member and fosters teamwork by inter-group coordination within the modules of the project.
• Effectively collaborates and communicates with the stakeholders and ensure client satisfaction
• Train and coach members of project groups to ensure effective knowledge management activity.
  
  

Certifications Needed

• Azure Data Bricks
• ITIL Foundation
  
  

About Mphasis

Mphasis applies next-generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis' Front2Back Transformation approach. Front2Back uses the exponential power of cloud and cognitive to provide hyper-personalized (C=X2C2TM=1) digital experience to clients and their end customers. Mphasis' Service Transformation approach helps 'shrink the core' through the application of digital technologies across legacy environments within an enterprise, enabling businesses to stay ahead in a changing world. Mphasis' core reference architectures and tools, speed and innovation with domain expertise and specialization are key to building strong relationships with marquee clients.