Data Engineer

Job Description

We re transforming the software industry. We re Flexera. With more than 50,000 customers across the world, we re achieving that goal . But we know we can t do any of that without our team . Ready to help us re-imagine the industry during a time of substantial growth and ambitious plansCome and see why we re consistently recognized by Gartner, Forrester and IDC as a category leader in the marketplace. Learn more at flexera.com Job Summary: We are seeking a skilled and motivated Senior Data Engineer to join our Automation, AI/ML team. In this role, you will work on designing, building, and maintaining data pipelines and infrastructure to support AI/ML initiatives, while contributing to the automation of key processes. This position requires expertise in data engineering, cloud technologies, and database systems, with a strong emphasis on scalability, performance, and innovation. Key Responsibilities: Identify and automate manual processes to improve efficiency and reduce operational overhead. Design, develop, and optimize scalable data pipelines to integrate data from multiple sources, including Oracle and SQL Server databases. Collaborate with data scientists and AI/ML engineers to ensure efficient access to high-quality data for training and inference models. Implement automation solutions for data ingestion, processing, and integration using modern tools and frameworks. Monitor, troubleshoot, and enhance data workflows to ensure performance, reliability, and scalability. Apply advanced data transformation techniques, including ETL/ELT processes, to prepare data for AI/ML use cases. Develop solutions to optimize storage and compute costs while ensuring data security and compliance. Required Skills and Qualifications: Experience in identifying, streamlining, and automating repetitive or manual processes. Proven experience as a Data Engineer, working with large-scale database systems (e.g., Oracle, SQL Server) and cloud platforms (AWS, Azure, Google Cloud). Expertise in building and maintaining data pipelines using tools like Apache Airflow, Talend, or Azure Data Factory. Strong programming skills in Python, Scala, or Java for data processing and automation tasks. Experience with data warehousing technologies such as Snowflake, Redshift, or Azure Synapse. Proficiency in SQL for data extraction, transformation, and analysis. Familiarity with tools such as Databricks, MLflow, or H2O.ai for integrating data engineering with AI/ML workflows. Experience with DevOps practices and tools, such as Jenkins, GitLab CI/CD, Docker, and Kubernetes. Knowledge of AI/ML concepts and their integration into data workflows. Strong problem-solving skills and attention to detail. Preferred Qualifications: Knowledge of security best practices, including data encryption and access control. Familiarity with big data technologies like Hadoop, Spark, or Kafka. Exposure to Databricks for data engineering and advanced analytics workflows.