6 months ago
Base Salary
$107k - $161k/yr
Responsibilities
- Design, develop, and maintain scalable data pipelines for structured and unstructured data using Big Data technologies.
- Implement and optimize ETL/ELT processes for ingestion, cleansing, transformation, and loading into data warehouses, data lakes, and other data stores.
- Build data federation layers supporting lambda and Data Mesh architectures, including solutions using Starburst.
- Develop and deploy microservices-based architectures for scalable, resilient, and maintainable data-intensive applications.
- Apply AI and ML techniques such as machine learning, deep learning, and natural language processing to business use cases.
- Ensure data quality, integrity, and security throughout the data lifecycle.
- Contribute to data engineering standards, processes, best practices, feasibility studies, implementation planning, testing, and operational support.
- Analyze complex application and business process issues, recommend programming solutions, and communicate technical concepts to technical and non-technical audiences.
- Assess technology and compliance risks, establish operating standards, and supervise or create accountability for relevant activities.
Requirements
- Bachelor’s degree in computer science, engineering, or a related field; a master’s degree is a plus.
- 8+ years of experience in Big Data or large-scale enterprise application development using technologies such as Databricks, Scala, Java, and Python.
- At least 5 years of experience in a data engineering lead role focused on Big Data, data federation, data extraction, and Data Mesh architecture.
- Deep understanding of data modeling, data warehousing concepts, methodologies, and best practices.
- Expertise designing, building, and maintaining data pipelines with Hadoop, Spark, Hive, Kafka, and related ecosystems.
- Proficiency in Python, Java, or Scala and strong SQL skills with relational database experience.
- Hands-on experience with ETL/ELT tools and microservices frameworks, plus familiarity with containerization technologies.
- Practical experience applying AI/ML techniques to real-world problems.
- Experience in systems analysis, software application programming, project implementation, and managing deadlines or changing requirements.
- Preferred experience with Cloudera, Databricks, AWS, Azure, or GCP; banking retail products; relevant technology certifications; or open-source and data engineering community contributions.
- Strong communication, collaboration, problem-solving, independent judgment, and teamwork skills.
Benefits
- Full-time position based in Irving, Texas.
- Base salary range of $107,120.00-$160,680.00 per year, 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.
- Anticipated posting close date is May 26, 2026.
Tech Stack
Apache HadoopApache HiveApache KafkaApache SparkAWSAzureDatabricksDockerGoogle Cloud PlatformJavaKubernetesPythonScalaSQL
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.