Manager - Data Engineering

Role Overview: You have over 8 years of experience delivering software or data solutions using Agile, Lean, and DevSecOps practices. You possess 3+ years of direct people leadership experience managing engineering teams, with a preference for data engineering. Your proven ability includes building and sustaining high-performing, inclusive teams and leading through change such as modernization, cloud adoption, and data platform transformation. You excel in execution leadership by setting clear goals, making timely decisions, managing risk, and honoring commitments across multiple initiatives. Additionally, you have experience influencing and partnering in matrixed environments with various stakeholders, and experience in financial services or insurance industry is preferred. Key Responsibilities: - Strong, hands-on background in data engineering, including building and operating data pipelines, data products, and data platforms. - Designing and reviewing data solution designs, data models, and pipeline implementations, challenging trade-offs, and providing technical guidance to engineers. - Designing and running data workloads on major cloud platforms, using services such as object storage, data integration, compute, and orchestration. - Experience with Databricks or similar Spark-based platforms for large-scale batch and streaming data processing, including cluster configuration and performance optimization. - Designing data solutions for scalability, resiliency, and performance, including partitioning, clustering, caching, schema evolution, and cost optimization practices. - Proficiency in modern programming languages for data engineering such as Python, Scala, or Java. - Strong experience with SQL for data transformation, analysis, and performance tuning. - Experience with Git-based workflows and CI/CD pipelines for data engineering. - Automating data quality and governance gates as part of delivery pipelines. - Strong understanding of data security and privacy practices, encryption, key management, access control, data masking, and compliance with regulations. - Integrating data platforms with upstream and downstream systems via various mechanisms and ensuring reliable operations with observability tooling. - Nice to have skills include experience with additional data tools and frameworks, exposure to machine learning, analytics, or BI use cases, and enabling self-service data consumption for analysts and data scientists. Qualifications Required: - Over 8 years of experience delivering software or data solutions using Agile, Lean, and DevSecOps practices. - 3+ years of direct people leadership experience managing engineering teams, with a preference for data engineering. - Proven ability to build and sustain high-performing, inclusive teams and lead through change. - Experience influencing and partnering in matrixed environments with various stakeholders. - Proficiency in modern programming languages for data engineering. - Strong experience with SQL for data transformation, analysis, and performance tuning. - Strong understanding of data security, privacy practices, and compliance requirements. - Experience integrating data platforms with upstream and downstream systems. - Familiarity with observability tooling and practices for data systems to support reliable operations and fast incident response. (Note: Any additional details of the company were not provided in the job description.) Role Overview: You have over 8 years of experience delivering software or data solutions using Agile, Lean, and DevSecOps practices. You possess 3+ years of direct people leadership experience managing engineering teams, with a preference for data engineering. Your proven ability includes building and sustaining high-performing, inclusive teams and leading through change such as modernization, cloud adoption, and data platform transformation. You excel in execution leadership by setting clear goals, making timely decisions, managing risk, and honoring commitments across multiple initiatives. Additionally, you have experience influencing and partnering in matrixed environments with various stakeholders, and experience in financial services or insurance industry is preferred. Key Responsibilities: - Strong, hands-on background in data engineering, including building and operating data pipelines, data products, and data platforms. - Designing and reviewing data solution designs, data models, and pipeline implementations, challenging trade-offs, and providing technical guidance to engineers. - Designing and running data workloads on major cloud platforms, using services such as object storage, data integration, compute, and orchestration. - Experience with Databricks or similar Spark-based platforms for large-scale batch and streaming data processing, including cluster configuration and performance optimization. - Designing data solutions for scalability, resiliency, and performance, including partitioning, clustering, ca