Senior Analyst - Data Engineering

Sr. Analyst – Data Engineering

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About Inizio Ignite:

Inizio Ignite is the global advisory partner for health and life sciences, encompassing connected expertise across Research Partnership, Putnam, Vynamic, and STEM. Guided by purpose, passion, and precision, we collaborate with clients to ignite impact, accelerate performance, and deliver lasting change for patients. By uniting strategy, insights, and innovation with a unique depth and breadth of expertise, we drive transformation and shape the future of health.

Company Descriptor

Inizio Ignite is the global advisory partner for health and life sciences, encompassing connected expertise across Research Partnership, Putnam, Vynamic, and STEM. Guided by purpose, passion, and precision, we collaborate with clients to ignite impact, accelerate performance, and deliver lasting change for patients. By uniting strategy, insights, and innovation with a unique depth and breadth of expertise, we drive transformation and shape the future of health. Our Research Partnership healthcare market research team provides research and insights to inform and power healthcare decisions. Serving a variety of clients across the lifecycle, our expertise includes data, research & insights (proprietary syndicated and custom research) and brand tracking (ATU). Proudly part of Inizio – the market-leading commercialization partner for health and life sciences. From early-stage development to loss of exclusivity, we simplify complexity, unlock value, and make collaboration seamless at every pivotal moment – supporting confident, insight-driven decisions that move innovation forward.

Role Overview

We’re looking for a Data Engineer with strong expertise in building scalable data platforms and pipelines. You’ll work with modern cloud ecosystems and distributed systems to enable efficient, data-driven decision-making across the full data lifecycle.

What you'll be doing

• Design, build, and optimize data pipelines for ingestion, transformation, and consumption.
• Develop scalable ETL/ELT workflows, ensure data quality and governance, and support large-scale data processing.
• Collaborate with teams to deliver reliable and efficient data solutions.

What you'll need

• Strong experience in PySpark, SQL, and data pipeline development.
• Proficiency with cloud platforms (AWS, Azure, or GCP) and data warehousing tools like Snowflake.
• Hands-on experience with Airflow, dbt, and distributed computing frameworks such as Spark.
• Solid understanding of data modeling, data lifecycle management, and governance practices.

Ideal candidate should be

• Exposure to streaming tools like Kafka, containerization with Docker, and CI/CD pipelines.
• Basic understanding of AI/ML workflows and concepts like RAG is a plus.