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Requirements: airflow, dbt, Snowflake, AWS, Python, SQL. Develop advanced data pipelines leveraging dbt, Airflow, and Snowflake, prioritizing performance optimization and data integrity using Great Expectations. Lead architectural design sessions for our modern data stack, ensuring seamless integration with Snowflake, Airflow, dbt, Great Expectations, and AWS data services. 5+ years in pivotal Software/Data Engineering roles, with expertise in Snowflake, Airflow, dbt, and AWS. Proficient in Python and SQL for complex data operations and transformations

senior data engineer

Job Details: <ul> <li>Title: Sr. Data Engineer</li> <li>Salary: $160K - $180K</li> <li>Requirements: airflow, dbt, Snowflake, AWS, Python, SQL</li> <li>Location: 100% Remote</li> </ul> Our client, a personal finance startup, is seeking a Sr. Data Engineer to join their team. This role entails spearheading the evolution and upkeep of the Enterprise Data Platform - this includes overseeing a cutting-edge Serverless Data Lake, a Cloud Data Warehouse hosted on AWS, and critical data and application pipelines. If you are looking to broaden your responsibilities, take on various leadership challenges, and propel your career growth, this is the opportunity you've been waiting for! Responsibilities: <ul> <li>Develop advanced data pipelines leveraging dbt, Airflow, and Snowflake, prioritizing performance optimization and data integrity using Great Expectations</li> <li>Lead architectural design sessions for our modern data stack, ensuring seamless integration with Snowflake, Airflow, dbt, Great Expectations, and AWS data services</li> <li>Collaborate with data science and product management teams to design, prototype, and launch new data products swiftly</li> <li>Tackle intricate challenges with innovative, streamlined solutions, prioritizing reliability, scalability, quality, and cost-effectiveness</li> <li>Establish processes for data transformation, metadata management, and workload optimization</li> <li>Partner with the team to conduct root cause analyses and audit internal and external data and processes to address specific business inquiries</li> </ul> Requirements <ul> <li>Master's (or B.S. with industry experience) in math, statistics, computer science, or related field</li> <li>5+ years in Dimensional Data Warehousing/Data Modeling and 'Big Data'</li> <li>5+ years in pivotal Software/Data Engineering roles, with expertise in Snowflake, Airflow, dbt, and AWS</li> <li>Proficient in Python and SQL for complex data operations and transformations</li> <li>Experienced in data quality assurance frameworks, particularly Great Expectations</li> <li>Collaborates with data analytics to align business needs</li> <li>Familiar with AWS infrastructure</li> <li>Strong problem-solving skills for agile environments</li> <li>Excellent communication and teamwork</li> <li>Curious and passionate about data and problem-solving</li> <li>Challenges data validity and assumptions</li> </ul>

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