Senior Data Engineer

Hyatt

. Collaborate with product managers, data scientists, engineering, and program management teams to define product features, business deliverables, and strategies for data products .

Posted 11/3/2026full-timeChicago • Illinois • United StatesSenior💰 $135,000 - $170,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing scalable data pipelines and data products, with a strong focus on cloud technologies and business intelligence tools. Proficient in data engineering practices, including data cleansing, validation, and advanced SQL, while effectively managing multiple projects in a collaborative environment.

Highest-signal resume keywords

Data Pipeline DevelopmentAWS Cloud TechnologiesBusiness Intelligence ToolsSQL ProficiencyData Warehousing Concepts

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

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

Hard Skills

Data Pipeline DevelopmentETL ApproachesData CleansingAdvanced SQLDimensional ModelingPython/Shell ScriptingInfrastructure as CodeData ValidationData WranglingAPI Development

Soft Skills

Analytical SkillsProblem-Solving SkillsCommunication SkillsAttention to DetailProject Management

Tools & Technologies

AWS GlueAWS LambdaAWS KinesisSnowflakeTableauInformatica IICSTerraformCloudFormationGitHub ActionsKafka

Industry Keywords

Data EngineeringBusiness IntelligenceBig DataCloud EnvironmentAgile/Scrum

Tech Stack

Tools & technologies

AWSCloudCognosDynamoDBETLInformaticaJenkinsKafkaNoSQLOraclePythonRDBMSSDLCShell ScriptingSnowflakeSQLTableauTerraform

About the role

Key responsibilities & impact

Collaborate with product managers, data scientists, engineering, and program management teams to define product features, business deliverables, and strategies for data products
Collaborate with business partners, operations, senior management, and other stakeholders on day-to-day operational support
Support operational reporting, self-service data engineering efforts, production data pipelines, and business intelligence suite
Gather and understand business requirements, assess feasibility and impact, and deliver on time with high quality
Design appropriate solutions and recommend alternative approaches when necessary
Research, prototype, and recommend emerging tools and technologies across cloud data engineering and Generative AI
Develop pipelines that process unstructured data, transform text, integrate models, and validate generated outputs for Generative AI initiatives
Work with high volumes of data, fine-tune database queries, and solve complex technical problems
Contribute to multiple projects and demands simultaneously
Work in a fast-paced, collaborative, iterative agile/Scrum environment
Exercise independent judgment in methods and techniques for obtaining results
Use state-of-the-art technologies to acquire, ingest, and transform big datasets
Lead multiple data projects with planned and coordinated execution and on-time delivery of quality products
Design, develop, and implement scalable and reliable data products and pipelines

Requirements

What you’ll need

8+ years of experience within the field of data engineering or related technical work including business intelligence, analytics
Experience designing and building scalable and robust data pipelines
Very good understanding of the full software development life cycle
Very good understanding of data warehousing concepts and approaches
Experience building data pipelines and ETL approaches
Experience building high-volume data workflows in a cloud environment
Experience building data warehouses and business intelligence projects
Experience in data cleansing, data validation, and data wrangling
Hands-on experience with AWS cloud and AWS native technologies such as Glue, Lambda, Kinesis, Lake Formation, S3, DynamoDB, Step Functions, Athena
Hands-on API development experience using AWS API Gateway, CloudWatch, Cognito, ECS, EKS, Fargate
Experience with business intelligence tools like Tableau, Cognos, ThoughtSpot
Experience with relational databases like Oracle and Snowflake, including advanced SQL, Tasks/Streams, stored procedures, and performance tuning
Hands-on experience with Snowflake Cortex AI, AI SQL functions or an equivalent production LLM platform
Proficient in SQL, PL/SQL, NoSQL, relational databases (RDBMS), database concepts, and dimensional modeling
Hands-on experience building complex business logic and data ingestion and transformation (ETL/ELT) workflows using Informatica IICS or similar tools, AWS pipelines, Snowpipe, streaming solutions, Kafka and other industry standard tools and processes is preferred
Hands-on experience with Python/shell scripting and SQL for building scalable data pipelines
Experience with CI/CD tools such as GitHub Actions and/or Jenkins
Experience with infrastructure as code using Terraform and/or CloudFormation
Experience implementing LLM observability with Arize or a comparable platform is a plus
Strong verbal and written communication skills
Demonstrated analytical and problem-solving skills, particularly in Data Warehouse and Big Data environments
Ability to manage multiple projects and report simultaneously across different stakeholders
Rigorous attention to detail and accuracy
Bachelor's degree in engineering, Computer Science, Statistics, Economics, Mathematics, Finance, or a related quantitative field is preferred

Benefits

Comp & perks

Annual allotment of free hotel stays at Hyatt hotels globally
Flexible work schedule
Work-life benefits including wellbeing initiatives such as a complimentary Headspace subscription
Discount at the on-site fitness center
Global family assistance policy with paid time off following the birth or adoption of a child
Financial assistance for adoption
Paid Time Off
Medical
Dental
Vision
401K with company match
Incentive awards and an annual bonus