Senior Data Engineer

About Us:

Fluent Health is a dynamic healthcare startup revolutionizing how you manage your healthcare and that of your family. The company will provide customers with high-quality, personalized options, credible information through trustworthy content, and absolute privacy. To assist us in our growth journey, we are seeking a highly motivated and experienced Senior Data Engineer to play a pivotal role in future success.

Company Website- https://fluentinhealth.com/

Job Description:

We're looking for a Senior Data Engineer to lead the design, implementation, and optimization of our analytical and real-time data platform. In this hybrid role, you'll combine hands-on data engineering with high-level architectural thinking to build scalable data infrastructure with ClickHouse as the cornerstone of our analytics and data warehousing strategy.

You'll work closely with engineering, product, analytics, and compliance teams to establish data best practices, ensure data governance, and unlock insights for internal teams and future data monetization initiatives.

Responsibilities:

Architecture & Strategy:

• Own and evolve the target data architecture, with a focus on ClickHouse for large-scale analytical and real-time querying workloads.
• Define and maintain a scalable and secure data platform architecture that supports various use cases including real-time analytics, reporting, and ML applications.
• Set data governance and modeling standards, and ensure data lineage, integrity, and security practices are followed.
• Evaluate and integrate complementary technologies into the data stack (e.g., message queues, data lakes, orchestration frameworks).

Data Engineering:

• Design, develop, and maintain robust ETL/ELT pipelines to ingest and transform data from diverse sources into our data warehouse.
• Optimize ClickHouse schema and query performance for real-time and historical analytics workloads.
• Build data APIs and interfaces for product and analytics teams to interact with the data platform.
• Implement monitoring and observability tools to ensure pipeline reliability and data quality.

Collaboration & Leadership:

• Collaborate with data consumers (e.g., product managers, data analysts, ML engineers) to understand data needs and translate them into scalable solutions.
• Work with security and compliance teams to implement data privacy, classification, retention, and access control policies.
• Mentor junior data engineers and contribute to hiring efforts as we scale the team.

Qualifications:

• 5-7 years of experience in Data Engineering, with at least 2-4 years in a Senior or Architectural role.
• Expert-level proficiency in ClickHouse or similar columnar databases (e.g., BigQuery, Druid, Redshift).
• Proven experience designing and operating scalable data warehouse and data lake architectures.
• Deep understanding of data modeling, partitioning, indexing, and query optimization techniques.
• Strong experience building ETL/ELT pipelines using tools like Airflow, dbt, or custom frameworks.
• Familiarity with stream processing and event-driven architecture (e.g., Kafka, Pub/Sub).
• Proficiency with SQL and at least one programming language like Python, Scala, or Java.
• Experience with data governance, compliance frameworks (e.g., HIPAA, GDPR), and data cataloging tools.
• Knowledge of real-time analytics use cases and streaming architectures.
• Familiarity with machine learning pipelines and integrating data platforms with ML workflows.
• Experience working in regulated or high-security domains like Healthtech, Fintech, or Enterprise SaaS.