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Position Summary This individual will contribute to the evolution of the enterprise DataHub/Delta Lake architecture, driving best practices in cloud-native, Spark-based data engineering. The ideal candidate has hands-on expertise with Databricks, AWS Cloud services, and Apache Spark (Python/Scala), and can serve as both a technical leader and mentor for junior engineers. What You Will Do: Architect and build robust, scalable, and secure data pipelines leveraging Databricks, Apache Spark, and AWS Cloud (EMR, Redshift, S3, Glue, Lambda). Participate and represent the data team in critical design discussions with technical leads across various product lines. Collaborate closely with application developers, product managers, and business analysts to translate requirements into data models, ETL/ELT workflows, and analytics-ready datasets. Conduct pull request reviews and enforce engineering excellence in code quality, testing, and performance optimization. Troubleshoot and optimize production data workflows while ensuring observability, resilience, and cost-efficiency at scale. Research, evaluate, and apply emerging tools and technologies to continuously modernize the data engineering ecosystem. Act as a mentor to junior engineers, fostering a culture of collaboration, innovation, and continuous learning. What You Will Bring: Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field. 7–10 years of professional data engineering experience, including at least 3+ years with modern cloud-based data lake architectures. Deep expertise in Apache Spark (PySpark, Scala, or Java) for large-scale distributed data processing. Strong experience with Databricks for collaborative data engineering and advanced analytics. Hands-on experience with AWS services including EMR, Redshift, S3, Glue, Lambda, IAM, and related cloud-native data tools. Proficiency in Python (preferred) as well as Java or Scala. Strong understanding of data modeling, data pipelines, and workflow orchestration (Airflow, Step Functions, or similar). NOGO experience Solid foundation in algorithms, data structures, and software engineering best practices. Excellent communication skills and a proven ability to work cross-functionally with product and engineering teams. *** ****Please note the interview process may entail an onsite finalist interview in Boston, MA. You'll Benefit From: At Careforth your well-being matters. With flexible schedules, a remote-first culture, and a nationally recognized wellness program, our benefits are designed to help you thrive, both professionally and personally. Discover how we invest in you: https://careforth.com/careers/#benefits The pay range for this position is $125K - $185K. The actual wage offered may be lower or higher depending on budget and candidate experience, knowledge, skills, qualifications, and geographic location. #LI-Remote (exceptions NYC, CA, and CO)