Data Engineer

Sr Data Engineer A Sr. Data Engineer is an experienced professional responsible for leading the development of complex data architectures. The role involves mentoring junior engineers, designing large-scale data solutions, and ensuring the reliability of data infrastructure. This position requires expertise in data engineering practices and a proactive approach to problem‑solving. Your Responsibilities on the Team Lead the design and implementation of scalable, high‑performance data architectures that support diverse data sources, including structured, semi‑structured, and unstructured data. Architect and build data pipelines that can process and analyze large‑scale datasets in real‑time and batch modes. Mentor and guide junior data engineers in best practices, code quality, and technical skills, fostering a culture of continuous learning. Ensure the reliability, efficiency, and security of data pipelines by implementing monitoring, alerting, and automated recovery mechanisms. Collaborate with cross‑functional teams, including data scientists, analysts, and product managers, to align data solutions with business needs and goals. Lead the adoption of new technologies and tools that enhance the data engineering capabilities of the team. Oversee the development of data models, schemas, and data marts that enable efficient data analysis and reporting. Implement data governance frameworks, including data lineage, metadata management, and data quality standards. Requirements Bachelor's degree in Computer Science, Information Technology, Management Information Systems, or a related field. 2-4 years of experience in data engineering or a related role, with demonstrated success in delivering data solutions. Proficient in SQL, with the ability to write complex queries, perform query optimization, and conduct performance tuning. Experience with cloud warehouses like Snowflake, Databricks, and an understanding of their appropriate use cases. Strong programming skills in Python, Java, or Scala, with experience in data processing frameworks (e.g., Apache Spark, Hadoop). Experience with cloud platforms (AWS, Azure, GCP) and data services, such as AWS Redshift, Azure Synapse, or Google BigQuery. Knowledge of big data technologies, including Hadoop, Spark, Kafka, and HBase, with experience in distributed data processing. Familiarity with data orchestration tools, such as MWAA for scheduling and managing data workflows. Nice to have experience with reporting tools such as Power BI and Tableau is a plus. Experience with data versioning and testing tools, such as DVC (Data Version Control) and dbt (data build tool). Understanding of data security practices, including encryption, access controls, and data masking. Familiarity with cloud administration in tools such as AWS, dbt, PowerBI, Tableau, and Snowflake is preferred. Lennar is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. #J-18808-Ljbffr