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Senior Analytics Programmer - REMOTE

Role overview

Qualifications

  • Bachelor's and Master's degree in Computer Science, Engineering, Data Science, Analytics, Economics, Statistics, Biostatistics, or a related quantitative field.
  • 1–2 years of hands-on experience in data engineering, analytics, software development, or related roles.
  • Strong working knowledge of SQL (required).
  • Experience coding in Python and/or R.

Responsibilities

  • Design, build, and maintain data pipelines to transform raw data into clean, structured analytical datasets.
  • Work with large datasets and apply data algorithms to support analytical workflows.
  • Develop scripts and workflows using Python or R for data processing and automation.
  • Write and optimize complex SQL queries for data extraction, transformation, and validation.

Key facts

Other skills

  • Problem Solving
  • Logical Reasoning
  • Detail Oriented
  • Communication
  • Collaboration
  • Quick Learning
  • Self-Motivation

About the company

JSR Tech Consulting logo

JSR Tech Consulting

JSR Tech Consulting provides contract consulting services for business and technology leaders in financial services, pharmaceuticals and healthcare. Our principals have close to 30 years of experience in supplemental services built on many long-term relationships. We can take on requirements of any kind: filling a single strategic position or supporting multimillion-dollar projects. JSR is also a certified Women-Owned Business Enterprise and an advocate of Disability:IN, a national non-profit supporting disability inclusion in the workplace and the supply chain.

Company details

Company size51 - 200

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Job description


Long Term contract position with a major Pharmaceutical firm. 

Remote position. (Preference given to candidates able to commute on as needed basis to Central Jersey. )

Experience Level: 1–2 Years
Position Overview
We are seeking a highly motivated, early-career Data Engineer to support a Life Sciences client in building and maintaining data pipelines, transforming real-world data into analytical-ready datasets, and supporting downstream analytics and reporting. This role is ideal for someone who enjoys hands-on coding, problem-solving, and learning in a fast-paced, data-driven environment.
The ideal candidate brings strong foundational technical skills, a logical and analytical mindset, and a genuine interest in growing long-term within data engineering and analytics. The client is willing to invest in training for candidates who demonstrate the right skills, curiosity, work ethic, and attitude.


Data Engineer (Life Sciences)


Required Qualifications
  • Bachelor's and Master's degree in Computer Science, Engineering, Data Science, Analytics, Economics, Statistics, Biostatistics, or a related quantitative field.
  • 1–2 years of hands-on experience in data engineering, analytics, software development, or related roles (internships and academic projects may be considered).
  • Strong working knowledge of SQL (required).
  • Experience coding in Python and/or R.
  • Experience working with large datasets and data transformation workflows.
  • Strong logical thinking and problem-solving skills.
  • Ability to understand and implement business rules and data logic accurately.
  • Self-driven, highly motivated, and eager to learn in a long-term role.
  • Fast learner with strong attention to detail and quality mindset.
  • Strong communication and collaboration skills.

Key Responsibilities
Data Engineering & Development
  • Design, build, and maintain data pipelines to transform raw data into clean, structured analytical datasets.
  • Work with large datasets and apply data algorithms to support analytical workflows.
  • Develop scripts and workflows using Python or R for data processing and automation.
  • Write and optimize complex SQL queries for data extraction, transformation, and validation.
  • Ensure data accuracy, consistency, and performance across pipelines.
Analytics & Reporting Support
  • Support the development of dashboards and reports for internal and client stakeholders.
  • Assist in translating business logic and rules into technical implementations.
  • Perform quality control checks and data validation to ensure reliable outputs.
  • Participate in exploratory analysis and research activities as needed.

 
 
What Success Looks Like
  • Quickly ramps up on data pipelines, tools, and business logic.
  • Produces clean, accurate, and reliable analytical datasets.
  • Writes efficient, maintainable code and SQL queries.
  • Demonstrates ownership, curiosity, and continuous improvement.
  • Collaborates effectively with team members and contributes ideas.
  • Grows into increased technical responsibility over time.
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Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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