
Lead Data Engineer | Azure Databricks and PySpark
Las Vegas, NVJob$120–135K/yrSeen 3 days agoSeen in employer's feed 3 days ago
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Job overview
Cognizant is seeking a hands-on Lead Data Engineer to design and develop high-performance data pipelines using Azure Databricks, Spark, and PySpark. The role leads data engineering solutions from design through production, establishes engineering practices, and partners with business and technical teams. It also includes mentoring engineers and optimizing data workloads. The posting requires 13+ years of data warehousing experience and 5+ years of Azure Databricks experience.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
Ready to build data platforms that actually make an impact?
We’re looking for a hands-on Lead Data Engineer who loves solving complex data problems and building scalable solutions with Azure Databricks, Spark, and PySpark .
You’ll lead the design and development of high-performance data pipelines, help shape engineering best practices, and work with teams across the business to turn data into meaningful insights.
What You’ll Do
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Design and build scalable data pipelines using Azure Databricks, Spark, and PySpark
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Lead end-to-end data engineering solutions from design through production
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Optimize Spark workloads, clusters, and jobs for performance, reliability, and cost
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Integrate data from multiple sources into trusted, analytics-ready datasets
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Build strong data quality, monitoring, and validation into every pipeline
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Establish coding standards, reusable frameworks, and engineering best practices
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Partner with architects, product teams, and business stakeholders to solve real-world data challenges
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Mentor engineers through design reviews, code reviews, and technical guidance
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Explore new Databricks and Spark capabilities and bring the best ideas into production
What We’re Looking For --> Must have 13+ years of total experience with DW space.
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Strong hands-on experience with Azure Databricks-- 5 + years-- Must have to be considered
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Deep expertise in Spark / PySpark, Python, and SQL
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Experience building large-scale ETL/ELT data pipelines
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Strong understanding of data modeling and distributed data processing
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Experience with performance tuning and Databricks cluster optimization
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Knowledge of Delta Lake, ADLS, ADF, Unity Catalog, CI/CD, and Azure DevOps is a plus
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Strong communication skills and the ability to lead and mentor engineering teams
Bonus Points
Experience working with hospitality, travel, booking, customer, or operational data .
If you enjoy building smart, scalable data solutions and want to see your work directly influence business and customer experiences, this could be a great fit.
Exempt Roles (up to AD Level)
Note: Compensation range should extend from the minimum to P75, consistent with the job family and level.
For all remote positions and those based in pay transparency locations, include this text in the External Description:
Salary and Other Compensation:
The annual salary for this position is between $120-135Kdepending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
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Medical/Dental/Vision/Life Insurance
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Paid holidays plus Paid Time Off
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401(k) plan and contributions
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Long-term/Short-term Disability
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Paid Parental Leave
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Employee Stock Purchase Plan
Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable la
Cognizant is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.
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