Engineer Senior - Data Engineering

Overview

Engineer Senior – Data Engineering

(7 to 10 years of experience in Data engineering)

We are Curious and We are Wipfli.

A top 20 consulting firm in the United States with 3,500 associates serving more than one lakh clients across industries. Through the last 90 years we have firmly remained committed to be always curious to discover ways for advancing, adapting, and getting the best possible solutions to our clients. 

Our services include Audit & Accounting, Tax, Business Consulting, Digital Transformation, Strategy & Operations, Litigation Support, Investment Banking among others. 

Join us to find a professional hub which is always striving to create a difference for the betterment of the global business environment. To know more about us and our offerings, please visit our website www.wipfli.com

Job Summary:

We are looking for an enthusiastic Data Engineers to join our experienced Data and Analytics team.  This role will take direction from the Enterprise Data Platform Team Director and will be responsible for contributing to the continuous advancement of a modern data lakehouse built to support a rapidly growing firm’s desire to democratize its data asset.

Essential responsibilities:

• Lead influence and consensus building efforts for recommended solutions
• Support and document the continued evolution of the firm’s data lakehouse using the medallion architecture
• Translate requirements into effective data models to support visualizations, AI\ML models, etc. leveraging design best practices and team standards using approved tools
• Develop data technologies such as Databricks, Microsoft Azure Data Factory, Python, T-SQL
• Manage the execution of project life cycle activities in accordance with the Information Team scrum processes and tools such as Microsoft Azure DevOps
• Achieve/maintain proficiency in required skills identified by the Information Team to effectively deliver defined products
• Collaborate with team members to evolve products and internal processes
• Mentor other Engineers and other IT associates as needed.
• Perform on-call support for after business hours as needed.

Ideal candidate profile Qualifications:  

• Demonstrated success in working on a modern data platform with Databricks experience being preferred. Accredited certification(s) and/or 5+ years hands on desired.
• Naturally curious with the ability to learn and implement new concepts quickly.
• A mastery of extracting and landing data from source systems via all access methods. Extra credit for Workday RaaS and/or Microsoft Dynamics/Dataverse skills.
• A commitment to operational standards, quality, and accountability for testing, code reviews/management and documentation.
• Engaged in virtual team experience leveraging video conferencing (cameras on) and a focus on relationship building. Travel is rare, but we do occasionally organize in-person events.

Data Architecture & Modeling

• Medallion architecture: Implementing and supporting layered data lakehouse structures (bronze, silver, gold).
• Data modeling: Translating requirements into logical and physical models for analytics, AI/ML, and visualization.
• Data governance: Ensuring compliance with standards, security, and quality in data design

Technical Development Skills

• Databricks: Proficiency in Databricks for scalable data engineering and AI/ML workflows, leveraging Delta Lake, Spark SQL; skilled in DABs (Databricks Asset Bundles) for CI/CD automation and deployment; and experienced with Terraform for infrastructure-as-code to provision and manage cloud resources efficiently.
• Azure Data Factory: Orchestrating ETL workflows and integrating diverse data sources.
• Python: Writing reusable scripts for automation, data wrangling, and ML integration.
• T-SQL: Query optimization, stored procedures, and database management.
• Azure DevOps: Managing backlog, CI/CD pipelines, and release management

Operational & Support Skills

• On-call support: Handling after-hours incidents and ensuring system reliability.
• Continuous learning: Achieving and maintaining proficiency in evolving technologies.
• Process improvement: Identifying opportunities to refine workflows and team practices

Skills

• Communication: Clear documentation, stakeholder updates, and technical writing.
• Problem-solving: Analytical thinking to troubleshoot complex data and system issues.
• Adaptability: Staying effective in dynamic environments with evolving tools and requirements.

Work location: Wipfli India, Bengaluru or Pune