Job Description
Job Title:  Technical Lead - DataBricks
City:  Minneapolis
State/Province:  Minnesota
Posting Start Date:  8/24/26
Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com.
Job Description: 

Job Description

Role: Technical Lead - DataBricks
Location: Dallas, TX (3 Days onsite/week)

 

Job Summary:
We are looking for a highly skilled and hands-on Databricks Lead Data Engineer to design, build, optimize, and manage scalable data engineering solutions using Databricks, Apache Spark, PySpark, SQL, and cloud-based data platforms. The ideal candidate should have strong technical leadership capabilities along with deep hands-on experience in developing production-grade data pipelines, lakehouse architectures, and enterprise data solutions.

 

Key Responsibilities:     
•    Lead the design, development, and implementation of scalable data pipelines and data lakehouse solutions using Databricks, PySpark, Spark SQL, and Delta Lake.
•    Work hands-on in building batch and streaming ETL/ELT pipelines from multiple source systems into cloud data platforms.
•    Design and implement medallion architecture layers such as Bronze, Silver, and Gold for efficient data processing and analytics consumption.
•    Optimize Spark jobs, Databricks notebooks, clusters, workflows, and SQL queries for performance, reliability, and cost efficiency.
•    Collaborate with business stakeholders, architects, data analysts, and data scientists to understand requirements and translate them into robust technical solutions.
•    Provide technical leadership, code reviews, best practices, and mentoring support to junior and mid-level data engineers.
•    Implement data quality checks, data validation rules, monitoring, logging, error handling, and restartability mechanisms.
•    Ensure adherence to data governance, security, access control, and compliance standards across data engineering solutions.
•    Support production deployments, troubleshoot pipeline failures, perform root cause analysis, and drive continuous improvement.

Required Skills:    
•    Strong hands-on experience in Databricks development, including notebooks, workflows, jobs, clusters, Delta Lake, and Unity Catalog.
•    Advanced programming experience in PySpark, Python, Spark SQL, and SQL.
•    Strong understanding of data engineering concepts, data warehousing, data lakehouse architecture, ETL/ELT design, and data modeling.
•    Experience in building scalable data pipelines on cloud platforms such as Azure, AWS, or GCP.
•    Hands-on experience with orchestration tools such as Azure Data Factory, Airflow, Databricks Workflows, or similar tools.
•    Experience working with file formats such as Parquet, Avro, JSON, CSV, and Delta format.
•    Good understanding of performance tuning techniques including partitioning, caching, broadcast joins, cluster sizing, compaction, and query optimization.
•    Experience with CI/CD, Git, DevOps practices, release management, and environment migration.
•    Strong troubleshooting, analytical, problem-solving, and communication skills.
•    Experience with Delta Live Tables, Structured Streaming, Auto Loader, Unity Catalog, and Databricks SQL.
•    Exposure to data governance, lineage, cataloging, masking, encryption, and role-based access control.
•    Experience in migration from legacy ETL tools or on-premise data warehouses to Databricks lakehouse platform.
•    Knowledge of cloud storage services such as ADLS, Blob Storage, S3, or Google Cloud Storage.
•    Experience in BFSI, healthcare, retail, or large enterprise data platform environments is an added advantage.
•    Databricks, Azure, AWS, or data engineering certifications are preferred.
Mandatory Skills: DataBricks - Data Engineering .

 

Experience: 5-8 Years .

 

The expected compensation for this role ranges from $60,000 to $135,000 .

 

Final compensation will depend on various factors, including your geographical location, minimum wage obligations, skills, and relevant experience. Based on the position, the role is also eligible for Wipro's standard benefits including a full range of medical and dental benefits options, disability insurance, paid time off (inclusive of sick leave), other paid and unpaid leave options.

 

Applicants are advised that employment in some roles may be conditioned on successful completion of a post-offer drug screening, subject to applicable state law.

 

Wipro provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Applications from veterans and people with disabilities are explicitly welcome.

 

Reinvent your world. We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention.
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