Data Solutions Engineer

This hybrid Data Solutions Engineer role at Citi offers the chance to shape next generation data platforms while working across cloud migration initiatives and cross-functional teams. The role is based in Irving, Texas with a listed opportunity in Jacksonville, Florida, and offers a competitive salary range of USD 107,120 to 160,680 per year. Citi provides a comprehensive benefits package that supports health, retirement, wellness, and work-life balance through discretionary and formulaic incentive programs, medical/dental/vision coverage, a 401(k), life and disability insurance, wellness programs, and paid time off.

Responsibilities

• As a core member of the Data Engineering team, design and build scalable Big Data solutions.
• Collaborate with domain experts, product managers, analysts, and data scientists to create robust pipelines in Hadoop or Snowflake environments.
• Deliver a data as a service framework to enable data accessibility and governance across the organization.
• Lead and execute the migration of all legacy workloads to cloud platforms, coordinating across stakeholders.
• Engage with stakeholders to elicit and document requirements, including detailed data flow specifications.
• Assess solution options and work with cross-functional teams to drive optimal implementations.
• Partner with data scientists to build pipelines from heterogeneous data sources and provide engineering services for data science applications.
• Research and evaluate open-source technologies, recommending and integrating suitable components into designs.
• Serve as a technical expert, mentoring teammates on Big Data and Cloud technology stacks.
• Define requirements for maintainability, testability, performance, security, quality, and usability across the data platform.
• Drive the implementation of consistent patterns, reusable components, and coding standards across data engineering processes.
• Convert SAS based pipelines into modern languages such as PySpark and Scala for Hadoop and non-Hadoop ecosystems.
• Optimize Big Data applications on Hadoop and non-Hadoop platforms for peak performance.
• Evaluate new IT developments and evolving business needs, recommending system enhancements aligned with industry standards.
• Assess risk and ensure compliance in decision making, safeguarding Citi, its clients, and assets while escalating and addressing control issues with transparency.

Requirements

• 5+ years of experience with Hadoop and Big Data technologies.
• Proficiency in Python, PySpark, and Scala, including hands-on experience with fundamental machine learning libraries.
• Experience building robust data solutions on Google Cloud or AWS; relevant certifications preferred.
• Experience with SAS.
• Experience with containerization and related technologies such as Docker and Kubernetes.
• Comprehensive understanding of software engineering and data analytics.
• Hands-on knowledge of the Hadoop ecosystem and Big Data technologies (HDFS, MapReduce, Hive, Pig, Impala, Kafka, Kudu, Solr).
• Knowledge of Agile (Scrum) development methodologies.
• Strong development and automation skills.
• System-level understanding of data structures, algorithms, distributed storage, and compute.
• A proactive approach to solving complex business problems, with strong interpersonal and teamwork skills.
• Bachelor’s degree in a related field.

Technologies

• Hadoop
• Snowflake
• Python
• PySpark
• Scala
• Google Cloud
• AWS
• SAS
• Docker
• Kubernetes
• HDFS
• MapReduce
• Hive
• Pig
• Impala
• Kafka
• Kudu
• Solr
• Java
• Apache Beam