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Senior Data Engineer (Chicago- Hybrid)
- Chicago, Illinois, United States
- Chicago, Illinois, United States
À propos
Hyatt seeks an experienced Senior Data Engineer who will be an exceptional addition to our growing engineering team. The Senior Data Engineer will work closely with engineering, product managers, and data science teams to meet the data requirements of various initiatives in Hyatt. As a Senior Data Engineer, you will take on big data challenges in an agile way, building data pipelines that enable engineers, analysts and other stakeholders across the organization, building data models to deliver insightful analytics, integrating different data sources, improving the efficiency, reliability, and latency of our data system, and leading multiple data projects with planned and coordinated execution and on-time delivery of quality products.
Who We Are At Hyatt, we believe in the power of belonging and creating a culture of care, where our colleagues become family. Since 1957 our colleagues and guests have been at the heart of our business and helped Hyatt become one of the best, and fastest growing hospitality brands in the world. Our transformative growth and the addition of new hotels, brands and business lines can open the door for exciting career and growth opportunities to our colleagues. We turn trips into journeys, encounters into experiences and jobs into careers.
How We Care for Our People What sets us apart is our purpose‑to‑care for people so they can be their best. Every business decision is made through the lens of our purpose, and it informs how we have and will continue to support each other as members of the Hyatt family.
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 and a discount at the on‑site fitness center
A global family assistance policy with paid time off following the birth or adoption of a child as well as financial assistance for adoption
Paid Time Off, Medical, Dental, Vision, 401(k) with company match
Who You Are As our ideal candidate, you understand the power and purpose of our culture of care, and embody our core values of Empathy, Inclusion, Integrity, Experimentation, Respect and Wellbeing. You enjoy working with others, are results driven, and seek a variety of opportunities to develop personally and professionally.
The Role
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, etc. on day‑to‑day operational support.
Support operational reporting, self‑service data engineering efforts, production data pipelines, and business intelligence suite.
Interface with multiple diverse stakeholders and gather/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.
Enable current Generative AI initiatives through the development of pipelines that process unstructured data, transform text, integrate models, and validate generated outputs.
Work with high volumes of data, fine‑tune database queries and solve complex technical problems.
Contribute to multiple projects/demands simultaneously.
Work in a fast‑paced, collaborative, and iterative environment.
Exercise independent judgment in methods and techniques for obtaining results.
Work in an agile/scrum environment.
Use state‑of‑the‑art technologies to acquire, ingest and transform big datasets.
Demonstrate a commitment to Hyatt's core values: respect, integrity, humility, empathy, creativity, and fun.
Qualifications
8+ years of experience within the field of data engineering or related technical work including business intelligence, analytics.
Experience and comfort solving problems in an ambiguous environment where there is constant change; have the tenacity to thrive in a dynamic, fast‑paced environment, inspire change, and collaborate with a variety of individuals and organizational partners.
Experience designing and building scalable and robust data pipelines to enable data‑driven decisions for the business.
Very good understanding of the full software development life cycle.
Very good understanding of data warehousing concepts and approaches.
Experience in building data pipelines and ETL approaches.
Experience in building high‑volume data workflows in a cloud environment.
Experience in building data warehouses and business intelligence projects.
Experience in data cleansing, data validation, and data wrangling.
Hands‑on experience in 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, 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, database concepts, and dimensional modelling.
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, and infrastructure as code with Terraform and/or CloudFormation.
Experience implementing LLM observability with Arize or a comparable platform is a plus.
Strong verbal and written communication skills.
Demonstrate integrity and maturity, and a constructive approach to challenges.
Demonstrate analytical and problem‑solving skills, particularly those that apply to data warehouse and big data environments.
Open‑minded, solution‑oriented and a very good team player.
Passionate about programming and learning new technologies; focused on helping yourself and the team to improve skills.
Effective problem‑solving and analytical skills.
Ability to manage multiple projects and report simultaneously across different stakeholders.
Rigorous attention to detail and accuracy.
Experience Preferred
Bachelor's degree in engineering, Computer Science, Statistics, Economics, Mathematics, Finance, or a related quantitative field.
The salary range for this position is $135,000-$170,000. This position is also eligible to earn an annual bonus. Pay for the successful candidate will meet local requirements, including the local minimum wage rate.
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Compétences linguistiques
- English
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