2 months ago
Base Salary
$126k - $189k/yr
Responsibilities
- Design, build, and maintain scalable ETL/ELT pipelines using PySpark, Spark SQL, Delta Lake, and Databricks.
- Implement and manage cloud data solutions across AWS, Google Cloud Platform, and Azure, using cloud-native storage, processing, and analytics services.
- Develop and optimize petabyte-scale data platforms using Databricks, Snowflake, Apache Iceberg, Starburst, and federated query strategies.
- Tune Spark workloads and Databricks clusters through job optimization, partitioning, caching, and autoscaling.
- Implement lakehouse architecture, data governance, schema evolution, data quality, lineage, security, and reliable data flows.
- Design data models and architectures supporting business intelligence, analytics, machine learning, and operational use cases.
- Provide data infrastructure and pipeline support for AI/ML, RAG, Agentic AI, and vector database use cases.
- Provide technical leadership, mentor junior engineers, and guide project workstreams and architectural decisions.
- Engage with clients and stakeholders, communicate project progress, manage expectations, and translate requirements into technical tasks.
- Participate in Agile and Scrum delivery activities including planning, stand-ups, and retrospectives.
Requirements
- Bachelor’s degree or university degree, or equivalent experience.
- 6–10 years of hands-on data engineering experience, preferably in a large-scale enterprise or financial services environment.
- Expert-level Python experience, including production data processing, automation, and API development.
- Extensive PySpark and Spark SQL experience, including DataFrame APIs and distributed-processing performance tuning.
- Experience with Databricks Lakehouse, Delta Lake, structured streaming, and Spark optimization.
- Practical experience with Ab Initio, including GDE, Co>Operating System, and Conduct>It.
- Hands-on Snowflake experience covering data warehousing, data modeling, RBAC security, performance tuning, Snowpipe, and Time Travel.
- Experience with Starburst or Trino and federated queries across disparate data systems.
- Familiarity with Apache Iceberg and open table formats.
- Multi-year experience with at least one major cloud provider and cloud-native data services.
- Experience building data pipelines for AI/ML models and understanding the machine learning data lifecycle.
- Demonstrated technical leadership, project-workstream leadership, mentoring, stakeholder management, client engagement, and project management skills.
- Experience as an Applications Development Manager or at a senior level in Applications Development.
- Knowledge of data governance, data quality, data security, industry practices, and standards.
- Relevant certifications such as AWS Certified Big Data, Google Professional Data Engineer, or Snowflake SnowPro are recommended.
- Experience with Docker and Kubernetes is recommended.
- Strong analytical, problem-solving, written, verbal communication, and independent-working skills.
Benefits
- Full-time position based in Irving, Texas.
- Base salary range of $125,760.00–$188,640.00, plus potential discretionary and formulaic incentive and retention awards.
- Medical, dental, and vision coverage; 401(k); life, accident, and disability insurance; and wellness programs.
- Paid vacation, sick leave, and holidays.
Tech Stack
Amazon RedshiftAWSAzureDatabricksDockerGoogle BigQueryGoogle Cloud PlatformKubernetesNumPyPandasPythonSnowflake
Categories
Data Engineering
About Citi
Citi is a public financial-services company offering consumer and institutional banking, credit cards, wealth management, treasury and trade solutions, and capital-markets services. It serves individuals, corporations, financial institutions, and governments in more than 160 countries and jurisdictions, earning interest and fee income from lending, payments, trading, and advisory. Founded in 1812 and headquartered in New York, it trades on the NYSE under the ticker C.