Health Catalyst
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Hyderabad · On-site · 2-5 Yrs · Sep 24
Healthcare Services & Hospitals · 1001 to 5000 Employees · Salt Lake City, US
Health Catalyst is a leading provider of data and analytics technology and services to healthcare organizations, committed to being the catalyst for massive, measurable, data-informed healthcare improvement. Health Catalyst serves over 600 healthcare clients including academic medical centers, integrated delivery networks, community hospitals, large physician practices, ACOs, health information exchanges, health insurers, and other risk-bearing entities. Its clients leverage the cloud-based data platform—powered by data from more than 100 million patient records and encompassing trillions of facts—as well as its analytics software and professional services expertise to make data-informed decisions and realize measurable clinical, financial and operatinal improvements. Health Catalyst has been recognized by Fortune, Gallup, Glassdoor, Modern Healthcare and others as a best place to work.
Hiring: Engineering
What employees say
+ Good company with great service
− Can give more bonuses with time
More reviews on the company profile.
Interview experience · Manager
2 interviews followed by cultural fitment round discussion. Easy interviews. simple and straight questions and nothing newly asked. They are not clear on the openings. It is a decent company.
Very_easy difficulty · India · 7 reports
More interview insightsJob description
Overview
We are looking for a Data Engineer – Analytics & AWS with 2–4 years of experience who enjoys working across both data engineering and data analytics.
Responsibilities
- Design, develop, and maintain ETL/ELT pipelines for data ingestion, transformation, and loading.
- Build and support data pipelines using AWS Glue and Amazon S3.
- Develop Python-based data processing and automation solutions.
- Build and optimize data warehouse solutions using Snowflake.
- Develop and support workflow orchestration using Airflow and related services.
- Work with event-driven and streaming workflows using Kafka.
- Troubleshoot production issues and improve pipeline performance, scalability, and reliability.
- Analyze data to identify trends, issues, and insights.
- Use SQL and Snowflake for data analysis, validation, and investigation.
- Support data quality and reconciliation activities across multiple data sources.
- Work with business and technical teams to understand analytics requirements.
- Translate data findings into practical technical solutions.
- Support analytics and reporting use cases across multiple projects.
- Work on projects across Data Ingestion, Data Transformation, Data Quality, and Data Analytics.
- Develop efficient SQL queries for transformation, validation, and analytics.
- Implement and maintain Snowflake capabilities including RBAC, ABAC, Snowpipes, and Dynamic Tables.
- Develop AWS Glue ETL workflows and Python Shell jobs.
- Work with AWS services including Glue, Lambda, SNS, and S3.
- Ensure data accuracy, consistency, security, and operational reliability.
- Investigate data issues and perform root‑cause analysis.
- Collaborate with engineers, analysts, and other stakeholders to understand requirements and deliver solutions.
- Document data processes, architecture, workflows, and operational procedures.
- Manage multiple projects and priorities based on business and team requirements.
- AWS
- AWS Glue
- AWS S3
- AWS Lambda
- AWS SNS
- Data & Analytics
- SQL
Qualifications
- 2–4 years of experience in Data Engineering, Analytics Engineering, Software Development, or a related field.
- Strong hands‑on experience with SQL and Python.
- Hands‑on experience with AWS Glue and S3.
- Working experience with Snowflake.
- Strong analytical, debugging, and problem‑solving skills.
- Ability to work on multiple projects and manage changing priorities.
- Strong collaboration and communication skills.
- An ownership mindset and attention to detail.
- Ability to learn new technologies and work effectively in a fast‑paced Agile environment.
- Exposure to AWS EMR, Redshift, Athena, Step Functions, IAM, CloudWatch, or EventBridge.
- Working knowledge of Kafka and streaming architectures.
- Familiarity with data lakes and distributed systems.
- Understanding of data governance, security, and access controls.
- Relevant certifications such as:
- SnowPro Advanced: Data Engineer
Education
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Why This Role?
- Join a collaborative Data Engineering team working on diverse projects across data ingestion, data transformation, data quality, and analytics. This role offers hands‑on exposure to both Data Engineering and Analytics, with opportunities to work with modern AWS, Snowflake, Python, and SQL technologies.
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Job application FAQ
Last updated 4 October 2026
- How do I apply for Data Engineer – Analytics & AWS at Health Catalyst?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Health Catalyst may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this Data Engineer – Analytics & AWS role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is Data Engineer – Analytics & AWS remote or on-site in Hyderabad, Telangana?
- This listing is marked on_site with location Hyderabad, Telangana. Confirm details on the job description before applying.
- What skills matter for this Data Engineer – Analytics & AWS role at Health Catalyst?
- This is a mid-level Data Engineer – Analytics & AWS role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.