Assemble large, complex data sets that meet functional and non-functional business requirements.
Identify, design, and implement process improvements, including automation, data delivery optimization, and infrastructure redesign for scalability.
Lead and deliver data-driven solutions across multiple languages, tools, and technologies.
Contribute to architecture discussions, solution design, and strategic technology adoption.
Build and optimize highly scalable data pipelines incorporating complex transformations and efficient code.
Design and develop new source system integrations from varied formats (files, database extracts, APIs).
Design and implement solutions for delivering data that meets SLA requirements.
Work with operations teams to resolve production issues related to the platform.
Apply best practices such as Agile methodologies, design thinking, and continuous deployment.
Develop tooling and automation to make deployments and production monitoring more repeatable.
Collaborate with business and technology partners, providing leadership, best practices, and coaching.
Mentor peers and junior engineers; educate colleagues on emerging industry trends and technologies.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent experience
7+ years of data engineering/development experience, including Python or Scala, SQL, and relational/non-relational data storage. (ETL frameworks, big data processing, NoSQL)
3+ years of experience in distributed data processing (Spark) and container orchestration (Kubernetes)
Proficiency in data streaming in Kubernetes and Kafka
Experience with cloud platforms – Azure preferred; AWS or GCP also considered.
Solid understanding of CI/CD principles and tools
Familiarity with big data technologies such as Hadoop, Hive, HBase, Object Storage (ADLS/S3), Event Queues.
Strong understanding of performance optimization techniques such as partitioning, clustering, and caching
Proficiency with SQL, key-value datastores, and document stores
Familiarity with data architecture and modeling concepts to support efficient data consumption
Strong collaboration and communication skills; ability to work across multiple teams and disciplines.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonScalaSQLETL frameworksbig data processingNoSQLSparkKubernetesKafkaHadoop

Soft Skills

leadershipcollaborationcommunicationmentoringcoachingproblem-solvingprocess improvementdesign thinkingbest practicesteamwork