Data Engineer

Real Chemistry; United States; On-site; USD 90,000 - 120,000; Full time

Benefits offered by this job

Comprehensive medical, dental, and vision plans

Paid time off

Mental wellness support

Access to online courses

Job summary

A leading healthcare technology company is seeking a Data Engineer to build and maintain scalable data pipelines that support AI products. This role involves collaborating with data scientists and product teams to ensure data quality across the organization. Required qualifications include a Bachelor's degree in a related field, 3–7 years of experience, and strong skills in SQL and Python. The position offers a comprehensive benefits program and opportunities for continuous improvement in a collaborative environment.

Qualifications

• 3–7 years of hands-on experience in data engineering or data pipeline development.
• Experience with streaming data tools such as Kafka or Kinesis is preferred.

Responsibilities

• Build, optimize, and maintain scalable ETL/ELT pipelines.
• Implement reliable and fault-tolerant ingestion and transformation workflows.
• Develop well-structured data models for analytics and ML use cases.
• Partner with data scientists and product managers to meet data requirements.

Skills

Strong SQL skills

Proficiency in Python or Scala

Data warehousing technologies (Snowflake, BigQuery, Redshift, Databricks)

Cloud services (AWS, Azure, GCP)

Data modeling and schema design

Distributed computing frameworks (Spark, Flink)

Workflow orchestration tools (Airflow, Prefect, Dagster)

Education

Bachelor’s degree in Computer Science, Data Engineering, or related field

Tools

AWS

Azure

GCP

Job description

Job Summary

We’re looking for a hands‑on Data Engineer to help build and maintain the data infrastructure that powers our AI products and solutions. This role sits within our AI organization and focuses on designing, developing, and optimizing scalable data pipelines, data models, and cloud‑based data systems. You’ll collaborate closely with data scientists, ML engineers, product teams, and other technical partners to ensure high‑quality, reliable, and well‑structured data is available across the organization.

Key Responsibilities

• Data Pipeline Development: Build, optimize, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
• Data Pipeline Development: Implement reliable, fault‑tolerant ingestion and transformation workflows.
• Data Pipeline Development: Automate routine data processes where possible.
• Data Architecture & Modeling: Develop well‑structured data models that support analytics, ML use cases, and downstream applications.
• Data Architecture & Modeling: Support design and enhancement of AI‑related data architecture across cloud environments.
• Data Quality & Governance: Implement automated data validation, monitoring, and alerting.
• Data Quality & Governance: Ensure high data accuracy, completeness, and integrity across ingestion and transformation layers.
• Cross‑Functional Collaboration: Partner with data scientists, ML engineers, product managers, and IT teams to understand data requirements and translate them into technical solutions.
• Cross‑Functional Collaboration: Troubleshoot issues and support stakeholders with data access and pipeline improvements.
• Cloud & Infrastructure: Work with modern cloud platforms (AWS, Azure, or GCP) and associated data storage, compute, and orchestration services.
• Cloud & Infrastructure: Support deployment, scaling, and operational health of data systems.
• Innovation & Continuous Improvement: Stay current with emerging data engineering tools and best practices.
• Innovation & Continuous Improvement: Propose opportunities to improve performance, efficiency, or reliability within the data stack.

Qualifications & Skills

Education & Experience

• Bachelor’s degree in Computer Science, Data Engineering, or related technical field (or equivalent experience).
• 3–7 years of hands‑on experience in data engineering or data pipeline development.

Technical Skills

• Strong SQL skills and proficiency in Python or Scala.
• Experience with data warehousing technologies such as Snowflake, BigQuery, Redshift, or Databricks.
• Hands‑on experience with cloud services (AWS, Azure, or GCP).
• Knowledge of data modeling, schema design, and ETL/ELT principles.
• Familiarity with distributed computing frameworks such as Spark or Flink.
• Experience with workflow orchestration tools like Airflow, Prefect, or Dagster is a plus.

Soft Skills

• Strong problem‑solving skills and attention to detail.
• Ability to communicate technical concepts clearly to peers and cross‑functional partners.
• Comfortable working in a fast‑moving, collaborative environment.

Preferred Qualifications

• Experience with streaming data tools such as Kafka or Kinesis.
• Experience building CI/CD pipelines for data workflows.
• Experience in healthcare, biotech, life sciences, or commercial/marketing data environments.
• Experience in agency or consulting settings.

Company & Benefits

Real Chemistry is proud to be Great Place to Work® certified and offers a comprehensive benefits program tailored to your region, including private medical, dental, and vision plans, paid time off, mental wellness support, and access to a wide range of online courses. Details vary by region. Visiting the benefits site provides role‑ and region‑specific information.

Equal Opportunity

Real Chemistry is an Equal Opportunity employer. We strive to build an inclusive and equitable work environment. Applicants are considered without regard to race, color, religion, sex (including pregnancy), sexual orientation, gender identity/expression, ethnic or national origin, age, physical or mental disability, genetic information, marital status, or any other characteristic protected by applicable laws. If accommodations are needed during the interview process, please let your recruiter know.