Sr Data Engineer

Overview

Lead design and implementation of scalable data architectures, pipelines, and mentorship.

Key Responsibilities

• data pipelines
• data governance
• monitoring
• data modeling
• data architecture
• tool adoption

Tasks

-Architect and build data pipelines that can process and analyze large-scale datasets in real-time and batch modes. -Implement data governance frameworks, including data lineage, metadata management, and data quality standards. -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. -Oversee the development of data models, schemas, and data marts that enable efficient data analysis and reporting. -Mentor and guide junior data engineers in best practices, code quality, and technical skills, fostering a culture of continuous learning. -Lead the adoption of new technologies and tools that enhance the data engineering capabilities of 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.

Requirements

• python
• sql
• aws
• spark
• snowflake
• bachelor's

What You Bring

-Knowledge of big data technologies, including Hadoop, Spark, Kafka, and HBase, with experience in distributed data processing. -2-4 years of experience in data engineering or a related role, with demonstrated success in delivering data solutions. -Bachelor's degree in Computer Science, Information Technology, Management Information Systems, or a related field. -Experience with cloud platforms (AWS, Azure, GCP) and data services, such as AWS Redshift, Azure Synapse, or Google BigQuery. -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). -Proficient in SQL, with the ability to write complex queries, perform query optimization, and conduct performance tuning. -Strong programming skills in Python, Java, or Scala, with experience in data processing frameworks (e.g., Apache Spark, Hadoop). -Familiarity with cloud administration in tools such as AWS, dbt, PowerBI, Tableau and Snowflake is preferred. -Familiarity with data orchestration tools, such as MWAA for scheduling and managing data workflows. -Understanding of data security practices, including encryption, access controls, and data masking. -Experience with Cloud warehouses like Snowflake, Databricks, and an understanding of their appropriate use cases.

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About Lennar

-Known for its focus on affordability and quality. -Builds homes in a wide range of communities from first-time homebuyers to luxury estates. -Integrates technology into homes, offering smart home solutions for modern living. -Notable projects include large-scale suburban communities and mixed-use developments, focusing on sustainability and convenience. -History includes several notable acquisitions, expanding its capacity to build homes nationwide. -Continues to innovate with a focus on reducing construction costs and increasing home energy efficiency. -Specializes in land development, mortgage services, and title insurance, creating a comprehensive approach to homebuilding.

Sector Specialisms