Job Description
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ZS is a place where passion changes lives
As a management consulting and technology firm focused on improving life and how we live it, we transform ideas into impact by bringing together data, science, technology and human ingenuity to deliver better outcomes for all
Here you’ll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers and consumers, worldwide
ZSers drive impact by bringing a client-first mentality to each and every engagement
We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business
Bring your curiosity for learning, bold ideas, courage and passion to drive life-changing impact to ZS.
Role Description
A Senior Data Engineer is a critical member of this team, specializing in designing, building, and maintaining systems and infrastructure that enable efficient processing, collection, storage, and analysis of large volumes of data
This role collaborates closely with business analysts, data scientists, and other stakeholders to ensure clean, accurate, and readily available data for informed decision-making and operational optimization.
What You’ll Do:
Design and build robust data models that align with business requirements.
Create scalable data architectures that accommodate growth and evolving data needs.
Develop and maintain data pipelines that facilitate seamless data flow from various sources to data warehouses or storage systems.
Optimize ETL (Extract, Transform, Load) processes for efficiency and reliability.
Implement and manage data storage solutions, including relational databases (e.g., SQL, PostgreSQL) and non-relational databases (e.g., MongoDB, Cassandra).
Set up and maintain data lakes for large-scale data storage.
Debug code issues / bugs using stack traces, logs, monitoring tools, and other resources.
Ensure data consistency and accuracy through validation and cleansing techniques.
Collaborate with cross-functional teams to address data-related issues.
Design and implement technical features leveraging best practices for technology stack being used.
Write production-ready code that is easily testable, understood by other developers and accounts for edge cases and errors.
Ensure highest quality of deliverables by following architecture/design guidelines, coding best practices, periodic design/code reviews and performing code/script reviews of senior engineers in the team.
Write unit tests as well as higher level tests to handle expected edge cases and errors gracefully, as well as happy paths.
Stay updated on industry trends and best practices in data engineering.
Provide guidance on data engineering tools, technologies, and methodologies.
Implement complex features with limited guidance from the engineering lead
For example: service or application-wide change.
Research & evaluate the latest technologies through rapid learning, conducting proof-of-concepts and creating prototype solutions.
Work closely with clients to understand their data engineering
Design and implement best-in-class data engineering solutions tailored to client projects.
Break down large features into estimable tasks, leads estimation and can align with clients.
Mentor junior Data Engineers, fostering their growth and skill development.
Collaborate with other technical teams to integrate data solutions seamlessly.
Participate in scrum calls and agile ceremonies, and effectively communicate work progress, issues, and dependencies.
Collaborate with client facing teams to understand solution context and contribute in technical requirement gathering and analysis.
Work with technical architects on the team to validate design and implementation approach.
A relevant Bachelors or higher-education degree in Computer Science, Data Science, or related fields.
Minimum 3+ relevant industry experience with big data - Hive, Spark, Hadoop, queueing system like Apache Kafka/Rabbit MQ/AWS Kinesis.
Hands-on experience in building metadata driven, reusable design patterns for data pipeline, orchestration, ingestion patterns (batch, real time).
- Experience in designing and implementation solutions on distributed computing and cloud services platforms (but not limited to) - AWS, Azure, GCP.
- Hands on experience building CI/CD pipelines and awareness of practices for application monitoring.
- Proficiency in programming languages such as Python, Java, or Scala.