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Lead / Sr. Data Engineer (Architect & Engineering Owner)
Lead / Sr. Data Engineer (Architect & Engineering Owner)
Mango Sciences's logo

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

Supriya C's profile picture
Posted by Supriya C
6 - 12 yrs
₹15L - ₹30L / yr
Remote only
Skills
skill iconPython
ETL
SQL
Database migration
Cloud transformation
Legacy to Cloud
Refactoring
Snowflake
databricks
Airflow
Prefect
Data Build Tool
Informatica
talend
SSIS
Big Data
HL7
FHIR
Claims data
Data Structures
Data Visualization
EHR integration
ICD-10
LOINC
Pharmacy data (Rx)
JSON
Performance tuning

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.


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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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About Mango Sciences

Founded :
2019
Type :
Product
Size :
20-100
Stage :
Raised funding

About

N/A

Company social profiles

N/A

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