Mango Sciences

Sr. DE / Data Engineer (Healthcare Data & SQL Expert)

Experience Level: 5–7 Years

Focus: Database Design, Advanced SQL, ETL/ELT Pipelines, and Healthcare Interoperability.

Summary

We are looking for a highly skilled Senior Data Engineer to join our healthcare data team. This role is perfect for a technical powerhouse who excels at building robust data pipelines and deeply understands database internals. You will be responsible for designing schemas, writing complex stored procedures, and optimizing SQL performance to handle clinical and claims data at scale. You will bridge the gap between raw data ingestion and high-performance analytics, ensuring all solutions meet HIPAA and FHIR standards.

What You’ll Do

1. Advanced SQL & Database Development

• Schema Design: Design and implement relational schemas (MSSQL, PostgreSQL, Oracle) ensuring data integrity through constraints, triggers, and normalized structures.
• Programmability: Write and maintain sophisticated Stored Procedures, Functions, and Views to handle complex business logic within the database layer.
• Performance Tuning: Own query optimization. You should be the expert in reading EXPLAIN/ANALYZE plans, implementing advanced indexing strategies (Clustered, Non-Clustered, Columnstore), and managing partitioning.
• Data Modeling: Build and manage dimensional models (Star/Snowflake) and implement Slowly Changing Dimensions (SCD Types 1, 2, and 4).
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2. Data Engineering & Ingestion

• Pipeline Development: Build and operate scalable ETL/ELT pipelines using Python and SQL to ingest data from EHRs, REST APIs, and flat files.
• Orchestration: Use Apache Airflow to schedule jobs, manage dependencies, and implement robust retry/alerting logic.
• API Integration: Develop Python-based ingestion frameworks that handle OAuth, pagination, and throttling for third-party healthcare data partners.

3. Healthcare Interoperability & Compliance

• Standards: Map complex clinical data to HL7 FHIR resources and curated analytic layers.
• Security: Implement "Privacy by Design" by enforcing HIPAA safeguards, including encryption at rest, access controls, and PII/PHI de-identification.

4. Operational Excellence

• CI/CD: Use GitHub and automated pipelines to deploy database changes and data code.
• Observability: Implement data quality tests (using tools like dbt or custom Python/SQL checks) to monitor freshness and accuracy.

What You’ll Bring

• Experience: 5–7 years of professional data engineering experience, with a heavy emphasis on backend database development.
• The SQL Expert Toolkit:
• Expert SQL: Window functions, CTEs, recursive queries, and set-based transformations.
• DB Internals: Deep knowledge of MSSQL, PostgreSQL, or Oracle. You should understand how the engine stores and retrieves data.
• Optimization: Proven track record of turning "slow" queries into high-performance assets via indexing and refactoring.
• The Engineering Toolkit:
• Python: Intermediate to advanced (Pandas/Polars, Requests, SQLAlchemy, or PySpark).
• Orchestration: Practical experience with Airflow (or Prefect/Dagster).
• Legacy/Cloud mix: Proficiency in SSIS/SSMA or PowerShell is a plus for migrating legacy workloads to modern platforms.
• The Domain Knowledge: Familiarity with FHIR/HL7 and an understanding of the importance of data governance in a regulated environment.

Technical "Must-Haves" for the Interview

• Ability to whiteboard a complex Database Schema from scratch.
• Ability to debug a long-running SQL query and explain the IO/CPU trade-offs of different index types.
• Experience handling JSON/BSON data types within a relational database context.

Nice to Have

• Experience with NoSQL systems like MongoDB or Elasticsearch.
• Cloud experience (Azure, AWS, or GCP) specifically regarding managed SQL services.
• Knowledge of dbt (data build tool) for managing transformations in the warehouse.

Lead / Sr. Data Engineer (Architect & Engineering Owner)

The Role

We are seeking a Lead Data Engineer who operates at the intersection of high-scale engineering and enterprise architecture. In this role, you will "own" our healthcare data platform end-to-end. You aren't just building pipelines; you are designing the blueprint for how clinical, claims, and sales data flow through our ecosystem. You will bridge the gap between legacy systems (MSSQL/Oracle) and modern cloud warehouses (Snowflake/Redshift/Databricks), ensuring our data is governed, HIPAA-compliant, and optimized for advanced analytics.

What You’ll Do

1. Architecture & Strategic Leadership

• Design the Blueprint: Own the enterprise data architecture (Staging, Integration, Warehouse, and Semantic layers). Define the evolution from monolithic databases to scalable cloud-hosted analytics.
• Modeling Mastery: Lead the design of complex Dimensional Models (Star/Snowflake) and implement advanced Slowly Changing Dimension (SCD) strategies to track historical clinical events.
• Set the Standard: Establish coding, version control (GitHub), and CI/CD standards. Conduct design reviews and mentor a team of engineers to move from "task-takers" to "system-builders."

2. Advanced Data Engineering (Hands-on)

• Modern ELT/ETL: Build and orchestrate production-grade pipelines using Python, Airflow, and dbt. Manage automated ingestion via Fivetran or custom-built frameworks for APIs and EHRs.
• Multi-Engine Expertise: Operate seamlessly across PostgreSQL, MSSQL, and Oracle, while optimizing petabyte-scale cloud warehouses like Snowflake or Redshift.
• Performance Tuning: Own query optimization. You should be the expert at using EXPLAIN/ANALYZE, partitioning, and indexing to reduce compute costs and latency.
• Quality & Reconciliation: Design robust validation frameworks to ensure data integrity—essential for healthcare compliance and clinical trust.

3. Healthcare Interoperability & Governance

• Data Standards: Map diverse datasets (EHR, API, Flat Files) to HL7 FHIR resources and curated analytic layers.
• Privacy by Design: Embed HIPAA Security Rule safeguards (encryption, audit trails, and access controls) directly into the code and infrastructure.
• Interoperability: Handle complex semi-structured data (JSON/XML) from third-party partners and EMR systems.

What You’ll Bring

• Experience: 8–12+ years in Data Engineering/Architecture. You should have a track record of leading technical projects or mentoring teams.
• The "Hybrid" Stack: * Expert SQL/PL-SQL: Deep experience with performance tuning in relational environments (Oracle/MSSQL).
• Modern Tools: Practical experience with Snowflake/Redshift, dbt, and Airflow.
• Programming: High proficiency in Python (Pandas, PySpark) or Java/Scala for custom ETL routines.
• Architectural Depth: Clear understanding of SDLC, Agile (Scrum), and Data Modeling frameworks.
• Healthcare Domain: Exposure to pharmaceutical or clinical data (Life Sciences, EMR, or Claims) is highly preferred.
• Soft Skills: The ability to translate "clinical business needs" into "technical runbooks" and communicate effectively with stakeholders.

Nice to Have

• AI/ML Integration: Experience supporting Data Science teams with feature extraction and model deployment (SageMaker/Azure ML).
• Advanced Tooling: Familiarity with NoSQL (MongoDB), search engines (Elasticsearch), or niche ETL tools (Talend/Informatica) for migration purposes.
• Cloud Infrastructure: Hands-on experience with AWS Glue, Lambda, or Azure Data Factory.

The Mission: We are looking for a visionary Technical Leader to own our healthcare data ecosystem from the first byte to the final dashboard. You won't just be managing a platform; you’ll be the primary architect of a clinical data engine that powers life-changing analytics. If you are an expert in SQL and Python who thrives on solving the "puzzle" of healthcare interoperability (FHIR/HL7) while mentoring a high-performing team, this is your seat at the table.

What You’ll Own

• Architectural Sovereignty: Define the end-to-end blueprint for our data warehouse (staging, marts, and semantic layers). You choose the frameworks, set the coding standards, and decide how we handle complex dimensional modeling and SCDs.
• Engineering Excellence: Lead by example. You’ll write production-grade Python for ingestion frameworks and craft advanced, set-based SQL transformations that others use as gold-standard references.
• The Interoperability Bridge: Turn the chaos of EHR exports, REST APIs, and claims data into clean, FHIR-aligned governed datasets. You ensure our data speaks the language of modern healthcare.
• Technical Mentorship: Act as the "Engineer’s Engineer." You’ll run design reviews, champion CI/CD best practices, and build the runbooks that keep our small but mighty team efficient.
• Security by Design: Direct the implementation of HIPAA-compliant data flows, ensuring encryption, auditability, and access controls are baked into the architecture, not bolted on.

The Stack You’ll Command

• Languages: Expert-level SQL (CTE, Window Functions, Tuning) and Production Python.
• Databases: Deep polyglot experience across MSSQL, PostgreSQL, Oracle, and NoSQL (MongoDB/Elasticsearch).
• Orchestration: Advanced Apache Airflow (SLAs, retries, and complex DAGs).
• Ecosystem: GitHub for CI/CD, Tableau/PowerBI for semantic layers, and Unix/Linux for shell scripting.

Who You Are

• Experienced: You have 8–12+ years in data engineering, with a significant portion spent in a Lead or Architect capacity.
• Healthcare-Fluent: You understand the stakes of PHI. You’ve worked with FHIR/HL7 and know how to map clinical resources to analytical models.
• Performance-Obsessed: You don’t just make it work; you make it fast. You’re the person who uses EXPLAIN/ANALYZE to shave minutes off a query.
• Culture-Builder: You believe in documentation, observability (lineage/freshness), and "leaving the campground cleaner than you found it."

Bonus Points for:

• Privacy Pro: Experience with PII/PHI de-identification and privacy-by-design.
• Cloud Native: Deep familiarity with Azure, AWS, or GCP security and data services.
• Search Experts: Experience with near-real-time indexing via Elasticsearch.

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