ETL

Data Engineer | AWS, Python & Snowflake | Ridgefield, CT (Hybrid) | $140K–$185K

🧠 Data Engineer

📍 Location: Ridgefield, Connecticut (Hybrid – 2–3 days onsite per week)
💼 Openings: 2
🏢 Industry: Information Technology / Life Sciences
🎓 Education: Bachelor’s degree in Computer Science, MIS, or related field (Master’s preferred)
🚫 Visa Sponsorship: Not available
🚚 Relocation: Available for the ideal candidate
💰 Compensation: $140,000 – $185,000 base salary + full benefits
🕓 Employment Type: Full-Time | Permanent

🌟 The Opportunity

Step into the future with a global leader in healthcare innovation — where Data and AI drive transformation and impact millions of lives.

As part of the Enterprise Data, AI & Platforms (EDP) team, you’ll join a high-performing group that’s building scalable, cloud-based data ecosystems and shaping the company’s data-driven future.

This role is ideal for a hands-on Data Engineer who thrives on designing, optimizing, and maintaining robust data pipelines in the cloud, while collaborating closely with architects, scientists, and business stakeholders across the enterprise.

🧭 Key Responsibilities

  • Design, develop, and maintain scalable ETL/ELT data pipelines and integration frameworks to enable advanced analytics and AI use cases.

  • Collaborate with data architects, modelers, and data scientists to evolve the company’s cloud-based data architecture strategy (data lakes, warehouses, streaming analytics).

  • Optimize and manage data storage solutions (e.g., S3, Snowflake, Redshift), ensuring data quality, integrity, and security.

  • Implement data validation, monitoring, and troubleshooting processes to ensure high system reliability.

  • Work cross-functionally with IT and business teams to understand data requirements and translate them into scalable solutions.

  • Document architecture, workflows, and best practices to support transparency and continuous improvement.

  • Stay current with emerging data engineering technologies, tools, and methodologies, contributing to innovation across the organization.

🧠 Core Requirements

Technical Skills

Hands-on experience with AWS data services such as Glue, Lambda, Athena, Step Functions, and Lake Formation.
✅ Strong proficiency in Python and SQL for data manipulation and pipeline development.
✅ Experience in data warehousing and modeling (dimensional modeling, Kimball methodology).
✅ Familiarity with DevOps and CI/CD practices for data solutions.
✅ Experience integrating data between applications, data warehouses, and data lakes.
✅ Understanding of data governance, metadata management, and data quality principles.

Cloud & Platform Experience

  • Expertise in AWS, Azure, or Google Cloud Platform (GCP) – AWS preferred.

  • Knowledge of ETL/ELT tools such as Apache Airflow, dbt, Azure Data Factory, or AWS Glue.

  • Experience with Snowflake, PostgreSQL, MongoDB, or other modern database systems.

Education & Experience

🎓 Bachelor’s degree in Computer Science, MIS, or related field
💼 5–7 years of professional experience in data engineering or data platform development
⭐ AWS Solutions Architect certification is a plus

🚀 Preferred Skills & Attributes

  • Deep knowledge of big data technologies (Spark, Hadoop, Flink) is a strong plus.

  • Proven experience troubleshooting and optimizing complex data pipelines.

  • Strong problem-solving skills and analytical mindset.

  • Excellent communication skills for collaboration across technical and non-technical teams.

  • Passion for continuous learning and data innovation.

💰 Compensation & Benefits

💵 Base Salary: $140,000 – $185,000 (commensurate with experience)
🎯 Bonus: Role-based variable incentive
💎 Benefits Include:

  • Comprehensive health, dental, and vision coverage

  • Paid vacation and holidays

  • 401(k) retirement plan

  • Wellness and family support programs

  • Flexible hybrid work environment

🧩 Candidate Snapshot

  • Experience: 5–7 years in data engineering or related field

  • Key Skills: AWS Glue | Python | SQL | ETL | CI/CD | Snowflake | Data Modeling | Cloud Architecture

  • Seniority Level: Mid–Senior

  • Work Arrangement: 2–3 days onsite in Ridgefield, CT

  • Travel: Occasional

🚀 Ready to power the future of data-driven healthcare?
Join a global data and AI team committed to harnessing the power of cloud and analytics to drive discovery, innovation, and meaningful impact worldwide.

Cloud Data Architect | AWS & Snowflake | Ridgefield, CT (Hybrid) | $170K–$210K

☁️ Cloud Data Architect

📍 Location: Ridgefield, Connecticut (Hybrid – 2–3 days onsite per week)
🏢 Industry: Pharmaceutical / Biotech / Information Technology
🎓 Education: Bachelor’s degree in Computer Science, Information Technology, or related field (or 10+ years equivalent IT experience)
💼 Experience Level: Mid–Senior (7–10 years)
🚫 Visa Sponsorship: Not available
🚚 Relocation: Available for ideal candidate
💰 Compensation: $170,000 – $210,000 base salary + benefits + potential performance bonus
🕓 Employment Type: Full-Time | Permanent

🌟 The Opportunity

Join a global leader in life sciences as a Cloud Data Architect, driving innovation and digital transformation within the Enterprise Data, AI & Platforms organization.

In this role, you’ll design and implement scalable, secure, and intelligent cloud-based data architectures that power analytics, AI, and digital products across the business. You’ll partner with data leaders, business stakeholders, and cross-functional technology teams to shape how data is collected, managed, and transformed into actionable insights.

If you’re passionate about modern data ecosystems, cloud architecture, and leveraging AI-driven solutions to impact patient outcomes — this is an opportunity to make a global difference.

🧭 Key Responsibilities

  • Design and implement efficient, scalable cloud-based data architectures that align with business and technology goals.

  • Develop and optimize data models, schemas, and database designs supporting structured and unstructured data.

  • Collaborate with business stakeholders, data domain owners, and data scientists to define data requirements and implement robust solutions.

  • Lead data modernization projects and support cloud migration strategies using AWS technologies.

  • Partner with governance teams to establish and maintain data policies, access frameworks, and sharing standards.

  • Enhance data pipelines for ingestion, transformation, and integration of diverse datasets across domains.

  • Provide technical leadership and mentorship to data engineering and development teams.

  • Stay ahead of emerging data technologies, AI/ML innovations, and architectural best practices to drive continuous improvement.

🧠 Core Qualifications

7+ years in data management and architecture, including experience as a Data Architect.
5+ years hands-on experience with cloud platforms (AWS required) and enterprise data solutions.
✅ Proven track record leading cloud modernization or data transformation projects.
✅ Strong experience with AWS components (S3, Glue, Lambda), Snowflake, Apache Parquet, and SQL/NoSQL databases.
✅ Proficiency with ETL tools such as dbt, SnapLogic, and middleware integrations.
✅ Expertise in data modeling, data pipeline optimization, and semantic data structures.
✅ Experience developing Knowledge Graphs and semantic data models using ontologies and taxonomies.
✅ Understanding of AI/ML data pipelines, including use cases in NLP, recommendation engines, and predictive analytics.
✅ Deep knowledge of data governance, quality, and lifecycle management.
✅ Excellent communication and collaboration skills to effectively engage technical and business teams.

💡 Preferred Skills & Certifications

AWS Solutions Architect certification (Associate or Professional).
⭐ Familiarity with Innovator or similar enterprise architecture tools.
⭐ Experience within pharmaceutical or biotech industries — particularly in commercial data domains or GxP environments.
⭐ Strong analytical and problem-solving mindset, with the ability to defend and present technical design decisions.
⭐ Exposure to Agile/Scrum delivery models and distributed global teams.

💰 Compensation & Benefits

💵 Base Salary: $170,000 – $210,000 (commensurate with experience)
🎯 Bonus: Role-specific or performance-based
💎 Benefits Include:

  • Comprehensive medical, dental, and vision coverage

  • Paid time off, holidays, and flexible hybrid schedule

  • 401(k) retirement plan with company match

  • Wellness, family support, and professional development programs

  • Global collaboration and mobility opportunities

🧩 Candidate Snapshot

  • Experience: 7–10 years in data architecture and cloud systems

  • Specialization: AWS Cloud | Data Modeling | ETL | Data Pipeline Design | Data Governance

  • Certifications: AWS Solutions Architect (preferred)

  • Seniority: Mid–Senior

  • Work Arrangement: 2–3 days onsite in Ridgefield, CT

  • Travel: Occasional

🌍 Why This Role Matters

This position sits at the heart of the company’s global data strategy — shaping how data is collected, structured, and leveraged to accelerate drug discovery, digital medicine, and patient outcomes. You’ll be part of a collaborative, innovation-driven environment where your work has a tangible impact on global healthcare advancements.

🚀 Ready to architect the future of cloud data innovation?
Join a team that’s transforming how data powers scientific breakthroughs and smarter decision-making — for patients, healthcare providers, and communities worldwide.

 

Senior Data Engineer - USA, Remote - $110,560 to $155,840

Senior Data Engineer

USA, Remote

$110,560 to $155,840

 

Job Description

You are a driven and motivated problem solver ready to pursue meaningful work. You strive to make an impact every day & not only at work, but in your personal life and community too. If that sounds like you, then you've landed in the right place.

The Data Science AI Factory team is committed to exploring new ways to use data and analytics to solve business problems.  The team utilizes a variety of data sources, with a strong focus on unstructured and semi-structured text using NLP to enhance outcomes related to claim, underwriting, operations and the customer experience. 

As a Sr. Data Engineer, you will be an established thought leader through close partnerships with expert resources to design, develop, and implement data assets for a wide range of new initiatives across multiple lines of business. The role involves heavy data exploration, proficiency with SQL and Python, knowledge of service-based deployments and APIs, and the ability to discover and learn quickly through collaboration.  There is a need to think analytically and outside of the box while questioning current processes and continuing to build on the individual’s business acumen.

There will be a combination of team collaboration and independent work efforts.  We seek candidates with strong quantitative background and excellent analytical and problem-solving skills. This position combines business and technical skills involving interaction with business customers, data science partners, internal and external data suppliers and information technology partners.

Responsibilities

  • Identify and validate internal and external data sources for availability and quality. Work with SME’s to describe and understand data lineage and suitability for a use case.

  • Create data assets and build data pipelines that align to modern software development principles for further analytical consumption. Perform data analysis to ensure quality of data assets.

  • Create summary statistics/reports from data warehouses, marts, and operational data stores.

  • Extract data from source systems, and data warehouses, and deliver in a pre-defined format using standard database query and parsing tools.

  • Understand ways to link or compare information already in our systems with new information.

  • Perform preliminary exploratory analysis to evaluate nulls, duplicates and other issues with data sources.

  • Work with data scientists and knowledge engineers to understand the requirements and propose and identify data sources and alternatives.

  • Produce code artifacts and documentation using Github for reproducible results and hand-off to other data science teams.

  • Propose ways to improve and standardize processes to enable new data and capability assessment and to enable pivoting to new projects.

  • Understand data classification and adhere to the information protection and privacy restrictions on data.

  • Collaborate closely with data scientists, business partners, data suppliers, and IT resources.

Experience & Skills

Candidates must have the technical skills to transform, manipulate and store data, the analytical skills to relate the data to the business processes that generates it, and the communication skills to document & disseminate information regarding the availability, quality, and other characteristics of the data to a diverse audience. These varied skills may be demonstrated through the following:

  • Bachelor’s degree or equivalent experience in a related quantitative field

  • 5 + years experience accessing and retrieving data from disparate large data sources, by creating and tuning SQL queries. Understanding of data modeling concepts, data warehousing tools and databases (e.g. Oracle, AWS, Snowflake, Spark/PySpark, ETL, Big Data, and Hive) 

  • Demonstrated ability to create and deliver high quality Python code using software engineering best practices. Experience with object-oriented programming and software development a plus. Proficiency with Github and Linux highly desired.

  • Ability to analyze data sources and provide technical solutions. Strong exploratory and problem-solving skills to check for data quality issues.

  • Determine business recommendations and translate into actionable steps 

  • Self-starter with curiosity and a willingness to become a data expert

  • Demonstrate a passion to both learn new skills and lead discovery of the data research 

  • Results oriented with the ability to multi-task and adjust priorities when necessary 

  • Ability to work both independently and in a team environment with internal customers 

  • Ability to articulate and train technical concepts regarding data to both data scientists and partners

Learn more