Life Science Connect
Staff Data Engineer (EL Focus - Azure/Snowflake)
Life Science Connect, Horsham, Pennsylvania, United States, 19044
About Life Science Connect
Life Science Connect is dedicated to uniting life sciences professionals and suppliers to accelerate research, development, and manufacturing We help professionals discover market opportunities by facilitating mutually beneficial connections between audiences and strategic partners. This accelerates the advancement of life-improving, life-extending, and life-saving therapies and devices. We serve a loyal, satisfied readership that demands original, compelling content with utility. Our comprehensive suite of capabilities for B2B sales and marketing enablement contributes significantly to the creation and maintenance of robust business development pipelines for our partners. The Mission: Data Force Multiplier
Life Science Connect is pivoting from a traditional publisher to a Data Authority. We are building a modern “Efficiency Stack” centered on Azure, Snowflake, and dbt to power our proprietary intent scoring and analytics products. Staff Data Engineer
This is a critical, high-impact role focused specifically on the Extraction and Load (EL) portion of our architecture. You will not just build pipelines; you will architect the ingestion framework that feeds our entire analytics ecosystem. Your success will be measured by your ability to deliver high-quality, reliable, and timely raw data to our Analytics Engineering team, acting as a force multiplier that enables them to focus purely on business logic and transformation. Key Responsibilities
EL Pipeline Architecture & Execution
Ingestion Architecture: Own the design, development, and optimization of scalable data ingestion pipelines using Azure Data Factory (ADF). Move beyond basic “drag-and-drop” configurations to build resilient, parameterized frameworks. Complex Source Integration: Design robust pipelines for high-volume, complex sources including Salesforce, Google Analytics (GA4), and internal APIs. Build custom connectors (using Python/Azure Functions) when native ADF connectors encounter API limits or sampling constraints. Snowflake Landing: Architect efficient loading patterns into Snowflake (Snowpipe, External Stages), ensuring that the “Raw Layer” is optimized for cost and performance before transformation begins.
Analytics Collaboration & Schema Governance
dbt Bridge: Act as the primary partner to the Analytics Engineering team. Collaborate on Raw Layer schema design, ensuring that data lands in a structure that is easily consumable by dbt, preventing “garbage in” scenarios. Data Reliability: Provide the downstream teams with thoroughly documented reliable raw data feeds. Guarantee that the data in the warehouse matches the source of truth.
Pipeline Orchestration & Optimization
Advanced Orchestration: Design dependency-aware pipeline orchestrations that manage the full data lifecycle, ensuring data arrives in the correct order and at the required frequency. Performance Tuning: Continuously monitor pipeline performance (latency, throughput) and optimize ADF resource allocation to control costs without sacrificing speed.
Engineering Standards & Security
CI/CD Implementation: Define and lead the implementation of CI/CD pipelines for data workflows. Enforce automated testing and deployment processes using Git/GitHub, treating infrastructure as code. Security & Compliance: Implement security best practices within the ingestion layer, specifically regarding Azure Key Vault for credential management and PIPL/GDPR compliance for PII handling.
The Ideal Candidate Profile
Experience
7+ years of professional experience in data engineering with a focus on high-volume production pipelines. Hybrid Skillset
Expert-level proficiency with Azure Data Factory (ADF) and strong coding skills. Proficient in Python and SQL, capable of writing custom scripts for API interactions, data validation, and complex logic that GUI tools cannot handle. API Mastery
Understand nuances of integrating with complex SaaS APIs (Salesforce, GA4). Handle rate limits, pagination, and token management programmatically. Warehouse Expertise
Extensive experience loading data into Snowflake and understand architectural implications of loading patterns on warehouse costs. Stakeholder Focus
Customer is the Analytics Engineer. Pride in delivering clean, reliable raw data that makes their job easier. Why Join Now?
Strategic Impact
Build the foundation of our “Data Authority” platform, handling the data that drives our revenue. Modern Stack
Work with a clean, modern stack—Azure, Snowflake, Python, and dbt—without the burden of on-prem legacy debt. Empowerment
Report to the Director of Data Architecture with a mandate to define the standards for how data enters our ecosystem. We Invest in YOU
At Life Science Connect, our commitment to empowering innovation and facilitating growth within the life sciences sector extends to our employees. We offer a comprehensive total compensation program designed to support your overall health, financial well-being, and professional development. In addition to a competitive salary, you’ll enjoy: Medical/vision/prescription/dental coverage for you and your family 100% company-paid short- and long-term disability insurance 100% company-paid life insurance 401(k) with dollar-for-dollar company match up to 6% 15 vacation days and 6 personal days on day 1 13 company-paid holidays Employment Notes
Principals only. No visa sponsorship is available for this position. No recruiter or staffing agency resumes accepted.
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Life Science Connect is dedicated to uniting life sciences professionals and suppliers to accelerate research, development, and manufacturing We help professionals discover market opportunities by facilitating mutually beneficial connections between audiences and strategic partners. This accelerates the advancement of life-improving, life-extending, and life-saving therapies and devices. We serve a loyal, satisfied readership that demands original, compelling content with utility. Our comprehensive suite of capabilities for B2B sales and marketing enablement contributes significantly to the creation and maintenance of robust business development pipelines for our partners. The Mission: Data Force Multiplier
Life Science Connect is pivoting from a traditional publisher to a Data Authority. We are building a modern “Efficiency Stack” centered on Azure, Snowflake, and dbt to power our proprietary intent scoring and analytics products. Staff Data Engineer
This is a critical, high-impact role focused specifically on the Extraction and Load (EL) portion of our architecture. You will not just build pipelines; you will architect the ingestion framework that feeds our entire analytics ecosystem. Your success will be measured by your ability to deliver high-quality, reliable, and timely raw data to our Analytics Engineering team, acting as a force multiplier that enables them to focus purely on business logic and transformation. Key Responsibilities
EL Pipeline Architecture & Execution
Ingestion Architecture: Own the design, development, and optimization of scalable data ingestion pipelines using Azure Data Factory (ADF). Move beyond basic “drag-and-drop” configurations to build resilient, parameterized frameworks. Complex Source Integration: Design robust pipelines for high-volume, complex sources including Salesforce, Google Analytics (GA4), and internal APIs. Build custom connectors (using Python/Azure Functions) when native ADF connectors encounter API limits or sampling constraints. Snowflake Landing: Architect efficient loading patterns into Snowflake (Snowpipe, External Stages), ensuring that the “Raw Layer” is optimized for cost and performance before transformation begins.
Analytics Collaboration & Schema Governance
dbt Bridge: Act as the primary partner to the Analytics Engineering team. Collaborate on Raw Layer schema design, ensuring that data lands in a structure that is easily consumable by dbt, preventing “garbage in” scenarios. Data Reliability: Provide the downstream teams with thoroughly documented reliable raw data feeds. Guarantee that the data in the warehouse matches the source of truth.
Pipeline Orchestration & Optimization
Advanced Orchestration: Design dependency-aware pipeline orchestrations that manage the full data lifecycle, ensuring data arrives in the correct order and at the required frequency. Performance Tuning: Continuously monitor pipeline performance (latency, throughput) and optimize ADF resource allocation to control costs without sacrificing speed.
Engineering Standards & Security
CI/CD Implementation: Define and lead the implementation of CI/CD pipelines for data workflows. Enforce automated testing and deployment processes using Git/GitHub, treating infrastructure as code. Security & Compliance: Implement security best practices within the ingestion layer, specifically regarding Azure Key Vault for credential management and PIPL/GDPR compliance for PII handling.
The Ideal Candidate Profile
Experience
7+ years of professional experience in data engineering with a focus on high-volume production pipelines. Hybrid Skillset
Expert-level proficiency with Azure Data Factory (ADF) and strong coding skills. Proficient in Python and SQL, capable of writing custom scripts for API interactions, data validation, and complex logic that GUI tools cannot handle. API Mastery
Understand nuances of integrating with complex SaaS APIs (Salesforce, GA4). Handle rate limits, pagination, and token management programmatically. Warehouse Expertise
Extensive experience loading data into Snowflake and understand architectural implications of loading patterns on warehouse costs. Stakeholder Focus
Customer is the Analytics Engineer. Pride in delivering clean, reliable raw data that makes their job easier. Why Join Now?
Strategic Impact
Build the foundation of our “Data Authority” platform, handling the data that drives our revenue. Modern Stack
Work with a clean, modern stack—Azure, Snowflake, Python, and dbt—without the burden of on-prem legacy debt. Empowerment
Report to the Director of Data Architecture with a mandate to define the standards for how data enters our ecosystem. We Invest in YOU
At Life Science Connect, our commitment to empowering innovation and facilitating growth within the life sciences sector extends to our employees. We offer a comprehensive total compensation program designed to support your overall health, financial well-being, and professional development. In addition to a competitive salary, you’ll enjoy: Medical/vision/prescription/dental coverage for you and your family 100% company-paid short- and long-term disability insurance 100% company-paid life insurance 401(k) with dollar-for-dollar company match up to 6% 15 vacation days and 6 personal days on day 1 13 company-paid holidays Employment Notes
Principals only. No visa sponsorship is available for this position. No recruiter or staffing agency resumes accepted.
#J-18808-Ljbffr