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Citi is seeking a highly skilled and experienced Senior Data Engineer to join our dynamic and innovative technology team. The ideal candidate will have a robust background in data engineering, with deep expertise in a variety of modern data technologies and a proven track record of working on large-scale data projects. This role will be pivotal in designing, building, and optimizing our data infrastructure on cloud platforms, and will also provide exposure to cutting-edge Artificial Intelligence projects, including Retrieval-Augmented Generation (RAG) and Agentic AI systems. The candidate must be proficient in Agile methodologies and possess strong leadership and client-facing skills to guide projects to successful completion while balancing stakeholder needs and organizational goals.
Job Responsibility:
Design, build, and maintain scalable ETL/ELT pipelines using PySpark, Spark SQL, and Delta Lake on Databricks
Implement and manage data solutions on cloud platforms
Work extensively with big data frameworks and platforms such as Databricks, Snowflake, and open table formats like Apache Iceberg
Optimize Spark workloads and Databricks clusters
Implement and manage Lakehouse architecture using Delta Lake
Lead the design and architecture of Starburst-based data solutions
Implement and manage data federation strategies using Starburst connectors
Identify and resolve performance bottlenecks in data pipelines and queries
Develop and optimize robust data pipelines with a strong focus on data governance
Design and implement data models that support business intelligence, analytics, and machine learning use cases
Partner with data scientists and AI specialists to support the development and deployment of AI models
Operate effectively within an Agile development environment
Provide technical leadership to steer the project in the right direction
Serve as a key point of contact for stakeholders and clients
Requirements:
Expert-level proficiency with Python and its data ecosystem (e.g., Pandas, NumPy, Dask). Extensive hands-on experience with the Spark framework, including deep knowledge of the DataFrame API, Spark SQL, and performance tuning techniques for distributed data processing
Proven experience developing on the Databricks Lakehouse Platform, including proficiency with Delta Lake, structured streaming, and optimizing Spark jobs within the Databricks environment
Strong, practical experience with the Ab Initio suite of products (GDE, Co>Operating System, Conduct>It) for designing and implementing enterprise-grade ETL workflows
Hands-on experience designing, building, and maintaining data warehouses in Snowflake
Experience using federated query engines like Starburst/Trino
Familiarity or experience with open table formats like Apache Iceberg for managing large analytic datasets
In-depth knowledge and multi-year experience with at least one major cloud provider (AWS, Google Cloud Platform, or Azure)
Practical experience building and managing data pipelines using cloud-native services such as AWS Glue, Lambda, S3, Redshift
Azure Data Factory, Synapse Analytics
or Google Cloud Composer, Dataflow, and BigQuery
A solid understanding of the data lifecycle required for machine learning projects
Experience in building data pipelines to support AI/ML models
Deep familiarity with Agile and Scrum methodologies
Demonstrated ability to provide technical leadership, influence architectural decisions, and steer projects towards successful outcomes
Exceptional communication and interpersonal skills, with proven proficiency in client interaction
6-10 years of hands-on experience in data engineering, preferably within a large-scale enterprise or financial services environment
Demonstrable experience leading project work streams and mentoring junior team members
Bachelor's degree/University degree or equivalent experience
Nice to have:
Relevant industry certifications (e.g., AWS Certified Big Data, Google Professional Data Engineer, Snowflake SnowPro)
Experience with containerization technologies like Docker and orchestration tools like Kubernetes
Deep understanding of data governance, data quality, and data security principles
Excellent analytical and problem-solving skills with the ability to work independently or as part of a team
Experience as Applications Development Manager
Experience as senior level in an Applications Development role
Stakeholder and people management experience
Demonstrated leadership skills
Proven project management skills
Basic knowledge of industry practices and standards
What we offer:
Medical, dental & vision coverage
401(k)
Life, accident, and disability insurance
Wellness programs
Paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays
Discretionary and formulaic incentive and retention awards