Lead Data Engineer

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What We'll Bring:

What You'll Bring:
We are looking for a Lead Data Engineer to join our growing Data Engineering and Analytics Practice who will drive building next generation suite of products and platform by designing, coding, building, and deploying highly scalable and robust solutions. You will be based both from our offices in Pune and working remotely as part of our ‘flex together’ approach. In this fast-paced role you will work with Business Stakeholders to achieve business goals. This exciting role will offer a host of development opportunities as part of a growing global business.

What You'll Bring:

Key Responsibilities:
 

• Design, build, test, and deploy innovative Big Data solutions at scale, including data lakes, data warehouses, and real-time analytics.
• Extract, clean, transform, and analyze vast amounts of raw data from various data sources.
• Build robust data pipelines and API integrations with various internal systems.
• Work across all stages of the data lifecycle, including data ingestion, storage, processing, and visualization.
• Implement best practices in data governance, security, and compliance across all data analytics processes.
• Estimate effort, identify risks, and plan execution effectively.
• Proactively monitor, identify, and escalate issues or root causes of systemic issues.
• Enable data scientists, business, and product partners to fully leverage our platform.
• Engage with business stakeholders to understand client requirements and build technical solutions and delivery plans.
• Evaluate and communicate technical risks effectively and ensure assignments are delivered on schedule with desired quality.
• Provide end-to-end big data solutions and design details to data engineering teams.
• Demonstrate excellent analytical and problem-solving skills.
• Exhibit excellent communication skills, with experience communicating with senior business stakeholders.
• Lead technical delivery on use cases, plan and delegate tasks to junior team members, and oversee work from inception to final product.
   

Skills & Experience:

Essential:

• Bachelor’s degree in Computer Science, Engineering, Statistics or a related field
• 8+ years of data engineering experience, with at least 3 years in senior roles.
• 5+ years of experience in Big Data technologies (e.g., Spark, Hive, Hadoop, Databricks).
• Strong experience designing and implementing data pipelines.
• Excellent knowledge of data engineering concepts and best practices.
• Proven ability to lead, mentor, inspire, and support junior team members.
• Ability to lead technical deliverables autonomously and guide junior data engineers.
• Strong attention to detail and adherence to best practices.
• Experience in designing solutions using batch data processing methods, real-time streams, ETL processes, and business intelligence tools.
• Experience designing logical data models and physical data models, including data warehouse and data mart designs.
• Strong SQL knowledge and experience (T-SQL, working with SQL Server, SSMS).
• Advanced proficiency with Apache Spark, including PySpark and SparkSQL, for distributed data processing.
• Working knowledge of Apache Hive.
• Proficiency in Python, Pandas, PySpark (Scala/Java knowledge is desirable).
• Knowledge of Delta Lake concepts and common data formats, Lakehouse architecture.
• Source control with Git.
• Expertise in designing and implementing scalable data pipelines and ETL processes using the GCP data stack, including BigQuery, Dataflow, Pub/Sub, Cloud Storage, Cloud Composer, Cloud Functions, Dataproc (Spark).
• Expertise in building and managing ETL workflows using Apache Airflow, including DAG creation, scheduling, and error handling.
• Knowledge of CI/CD concepts and experience designing CI/CD for data pipelines.
• Software engineering principles, including:
  • Object-oriented programming (OOP) principles.
  • Design patterns and their application in data engineering.
  • Software development lifecycle (SDLC).
  • Agile methodologies and practices.
  • Unit testing, integration testing, and test-driven development (TDD).
  • Performance optimization and scalability considerations.
     

Desirable:

• Experience with streaming services such as Kafka is a plus.
• R & Sparklyr experience is a plus.
• Knowledge of MLOps concepts, AI/ML lifecycle management, and MLflow.
• Expertise in writing complex, highly optimized queries across large data sets to write data pipelines and data processing layers.
• Jenkins experience is a plus.

Relevant certifications (e.g., Google Cloud Professional Data Engineer).
 

Impact You'll Make:

TransUnion – a place to grow:

We know that it is unrealistic to expect candidates to have each and every aspect of the essential and/or desirable skills listed above – if there is something you can’t tick off right now – good, you can learn here!

Impact you will make:

Enable Decision Making across the organization using data driven culture.

This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week.

TransUnion Job Title

Specialist IV, Data Science and Analytics