Sr Data Engineer

Responsibilities

• 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.
• 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.

Qualifications

• Experience with data engineering practices and a proactive approach to problem-solving.
• A career with purpose, including making dreams come true, building zero defect homes, cost management, and adherence to schedules.

Skills

• Data engineering practices.
• SQL proficiency.
• Cloud warehouses (Snowflake, Databricks).
• Programming languages (Python, Java, Scala).
• Data processing frameworks (Apache Spark, Hadoop).
• Data orchestration tools (MWAA).
• Data security practices.
• Cloud administration (AWS, dbt, PowerBI, Tableau and Snowflake).

Benefits

• Comprehensive health insurance plans (Medical, Dental, Vision).
• 401(k) Retirement Plan with a $1 for $1 Company Match up to 5%.
• Paid Parental Leave.
• Associate Assistance Plan.
• Education Assistance Program.
• Up to $30,000 in Adoption Assistance.
• Up to three weeks of vacation annually.
• Generous Holiday, Sick Leave, and Personal Day policies.
• New Hire Referral Bonus Program.
• Significant Home Purchase Discounts.
• Unique opportunities such as the Everyone’s Included Day.

Pay

TBD

Schedule

TBD