Data Engineer II

About the Role

As a Data Engineer, you are responsible for analyzing large amounts of business data, solving real world problems, and developing metrics and business cases that will enable Business Insights. This includes leveraging data from platforms such as Jira, Portal, and Salesforce, working with Product Managers, Software Engineers, and Business Intelligence Engineers to automate and scale the analysis and make data actionable  will own many large datasets, implement new data pipelines that feed into or from critical data systems.

• Design, implement and support an analytical data infrastructure and working knowledge of modern data warehouse concepts.
• Design, build, and maintain efficient and scalable data pipelines and ETL processes to process large volumes of structured and unstructured data.
• Optimize data storage and retrieval methods to ensure performance, scalability, and cost-efficiency.
• Manage AWS resources including EC2, S3, Glue, Lambda, API, IAM, and Cloud Watch.
• Interface with other technology teams to extract, transform, and load data from a wide variety of sources using SQL and AWS big data technologies.
• Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency.
• Collaborate with Data Scientists and Business Intelligence Engineers to recognise and adopt best practices in reporting and analysis.
• Help continually improve ongoing reporting and analysis processes, automating or simplifying self‑service support for customers.
• Maintain internal reporting platforms/tools, troubleshoot and develop, and interact with users to clarify requirements.
• Work with engineering partners to shape and implement the development of BI infrastructure including data warehousing, reporting, and analytics platforms.
• Contribute to the development of BI tools, skills, culture and impact.
• Write advanced SQL queries and Python code to develop solutions.
• Have working knowledge of Snowflake.
• Collaborate across teams to align AI initiatives with organisational goals and understanding of AI concepts.
• Understand continuous integration/continuous delivery pipelines and support deployments when necessary.

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• 3‑5 years of experience in data engineering or a related role, with demonstrated success in delivering data solutions.
• Experience with AWS Glue, Lambda, S3, EC2, Cloud Watch, and Cloud Trail.
• Experience with dbt, Snowflake, SQL, Python, and Qlik.
• Proficient in SQL, able to write complex queries, perform query optimisation, and conduct performance tuning.
• Experience with No
  
  SQL databases such as MongoDB, Cassandra, or DynamoDB and an understanding of their appropriate use cases.
• Strong programming skills in Python, Java, or Scala, with experience in data processing frameworks such as Apache Spark and Hadoop.
• Experience with cloud platforms (AWS, Azure, GCP) and data services such as AWS Redshift, Azure Synapse, or Google Big Query.
• Knowledge of big data technologies including Hadoop, Spark, Kafka, and HBase, with experience in distributed data processing.
• Familiarity with data orchestration tools such as Apache Airflow for scheduling and managing data workflows.
• Experience with data versioning and testing tools such as DVC and dbt.
• Understanding of data security practices, including encryption, access controls, and data masking.

Regular, in‑person attendance at the Lennar office during regular work hours is an essential function of this job. This is primarily a sedentary office position which requires the incumbent to have the ability to operate computer equipment, speak, hear, bend, stoop, reach, lift, and move and carry up to 25 lbs. Finger dexterity is necessary.

Lennar is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws.