Data Engineering Lead - Spark, Scala, AWS
Optum is a global organization that delivers care, aided by technology to help
millions of people live healthier lives. The work you do with our team will
directly improve health outcomes by connecting people with the care, pharmacy
benefits, data and resources they need to feel their best. Here, you will find
a culture guided by inclusion, talented peers, comprehensive benefits and
career development opportunities. Come make an impact on the communities we
serve as you help us advance health optimization on a global scale. Join us to
start
Caring. Connecting. Growing together.
Primary Responsibilities:
We are seeking a hands-on Technical Lead / Data Engineering
Leader with 7+ years of experience to design, build, and scale
enterprise-grade data platforms using Apache Spark, Scala, and AWS cloud
services. The ideal candidate will combine solid technical depth with
leadership capability to drive architecture, delivery, and team
excellence.
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Technical Leadership and Architecture
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Design and architect scalable, distributed data processing
systems using Spark and Scala.
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Define and implement cloud-native data architectures on
AWS (EMR, S3 etc.).
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Lead technical design reviews and enforce best practices
across teams.
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Drive system reliability, scalability, and security
standards across data platforms.
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Data Engineering and Platform Development
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Build and optimize step functions for large-scale batch
processing
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Develop high-performance solutions leveraging Spark (batch +
streaming) and Scala
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Enable ingestion and processing of structured, semi-structured,
and streaming data sources
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Ensure data quality, integrity, and governance across the
data lifecycle
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Cloud and DevOps Excellence
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Implement scalable solutions using AWS cloud ecosystem (EMR,
S3, Lambda etc.)
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Drive CI/CD, automation, and monitoring frameworks for data
pipelines
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Optimize pipelines for performance, cost, and fault tolerance
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Team Leadership and Delivery
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Lead and mentor a team of data engineers and developers, ensuring
high-quality delivery
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Drive Agile execution, sprint planning, and delivery commitments
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Collaborate with product managers, architects, and business
stakeholders to align solutions with business goals
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Foster a culture of code quality, ownership, and continuous
improvement
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Innovation and Strategy
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Evaluate and implement new technologies and tools to
optimize data platforms
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Work closely with data science teams to enable analytics, ML, and
AI use cases
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Contribute to data platform roadmap and modernization initiatives
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Comply with the terms and conditions of the employment contract, company
policies and procedures, and any and all directives (such as, but not
limited to, transfer and/or re-assignment to different work locations,
change in teams and/or work shifts, policies in regards to flexibility of
work benefits and/or work environment, alternative work arrangements, and
other decisions that may arise due to the changing business environment).
The Company may adopt, vary or rescind these policies and directives in
its absolute discretion and without any limitation (implied or otherwise)
on its ability to do so
Required Qualifications:
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Bachelor’s degree or equivalent experience
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6+ years of experience in Data engineering role
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Working experience on AWS Cloud
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Solid experience in using Spark & Scala
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Solid experience in Python, Kafka, MySQL, and Redis
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Experience with CI/CD tools (Jenkins), GitHub, and Snowflake
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Solid knowledge of data modeling, evaluating large data sets from multiple
sources and data transformation
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Proficient with AI Tools and Technologies like LLM’s, Agents, Vector
Database, Chatbots, etc.
Preferred Qualifications:
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Knowledge of data warehousing, distributed systems, and parallel computing
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Solid understanding of database concepts SQL and NoSQL and data processing
tools (Spark)
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Proven ability to work independently, mentor others, and lead initiatives
with minimal supervision
Proven excellent problem-solving skills and the ability to perform under
pressure