Lead Data Engineer

This job is with Thermo Fisher Scientific, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

Work Schedule

Standard (Mon-Fri) Environmental Conditions

Office

Job Description

Position Overview

As a Lead Data Engineer, your pivotal responsibility involves spearheading data initiatives and integrating top-tier data solutions. This role presents a thrilling chance to contribute to innovative projects and engage with a team of committed experts. Your proficiency is instrumental in elevating our competitiveness and ensuring seamless implementation of our data strategies!

Key Responsibilities

Lead the build, development, and optimization of scalable, secure, and high-performance data pipelines and architectures.

Lead and guide a team of data engineers and analysts, encouraging teamwork and technical excellence.

Implement standard methodologies for DataOps across the platform to uphold 99.99%+ availability, reliability, and recovery standards.

Build and maintain robust data models and frameworks, ensuring they align with enterprise architecture and governance standards.

Collaborate with cross-functional teams, including analytics, product, and business units to deliver high-impact, data-driven solutions.

Ensure data quality and validation through automated testing, monitoring, and anomaly detection techniques.

Own planning, prioritization, and execution of data engineering projects — delivering on time and within scope.

Contribute to platform scalability, performance tuning, and migration initiatives, including support for real-time data flows.

Deliver technical documentation and code reviews to uphold engineering standards and maintain knowledge continuity.

Support data privacy, security, and compliance requirements in line with global regulatory standards.

Qualifications

Bachelor's degree or equivalent experience in Computer Science, Data Engineering, Information Systems, or a related field.

Proven experience (5+ years) in data engineering with a strong understanding of modern data architecture, pipelines, and operations.

Expertise in ETL / ELT tools, data warehousing, and cloud-native platforms such as Databricks, Snowflake, or BigQuery.

Strong hands-on experience with SQL, Apache Spark, and Python (experience with Pandas preferred).

Proficient in working with large datasets and performance optimization for distributed computing environments.

Prior experience with tools like Informatica, Cognos, SQL Server, and Oracle is a strong plus.

Deep understanding of data modeling, metadata management, and data governance frameworks.

Demonstrated experience in leading engineering teams and managing project lifecycles.

Familiarity with DevOps / DataOps practices, version control systems (e.g., GitHub), and CI / CD pipelines.

Excellent communication, leadership, and collaborator management skills.

Experience working in cloud environments such as AWS, Azure, or GCP.

Why Join Us?

This is your chance to work on exceptionally impactful projects and grow your career in an encouraging and innovative environment!

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