Sr. Data Engineer (932110)

EXTERNAL POSTING

DUTIES:

Design, develop, and maintain scalable and reliable data pipelines to ingest, transform, and load structured, semi-structured, and unstructured data from various sources into our data lake and warehouse environments.  Implement data integration solutions to consolidate data from disparate sources, including databases, API’s, streaming platforms, and 3rd party services (e.g., Snowpipe, SnowPark, Dynamo, Kafka).  Optimize data processing workflows for performance, efficiency, and scalability using distributed computing or parallel processing frameworks such as FiveTran, dbt, Snowpark, Snowpipe.  Collaborate cross-functionally with IT & business stakeholders to understand data requirements, define data models, and develop solutions to support data services, reporting, and Software Development.  Partner with data, IT, and business teams to improve design and building of metrics to enhance our analytic capabilities.  Implement data quality checks, data validation processes, and error handling mechanisms to ensure the accuracy, completeness, and reliability of data across all stages of the data lifecycle.  Support the design and maintenance of data schemas, and metadata repositories for governance documentation of data lineage, definitions, and dependencies.  Support the development and maintenance of data governance policies, standards, and best practices to ensure compliance with data privacy regulations and industry standards.  Apply best practices for AWS and Snowflake architectures, data pipelines and data models.  Monitor, troubleshoot, and optimize the performance and availability of data systems and infrastructure using monitoring and logging tools such as Prometheus.  Stay current with emerging technologies, tools, and trends in data engineering, cloud architectures, and cloud computing to evaluate their potential impact and relevance to our data platforms.  Responsible to coach and mentor junior data engineers.  Hybrid work from home permitted two (2) days a week.

SCHEDULE:

40 hours per week, Monday through Friday

LOCATION:

Purpose Financial, Inc., 322 Rhett Street, Greenville, SC 29601

REQUIREMENTS:

Bachelor’s degree (or foreign equivalent degree) in Data Engineering, Applied Computer Science, Computer Applications or closely related field and five (5) years of experience as an Enterprise Data Engineer, ETL Developer, Technical Consultant or related occupation where required experience was gained.

SPECIAL SKILLS:

Also requires experience in the following:

• Data Engineering, data pipelines, and data services.
• Agile/Scrum based development and methodology.
• 3 years of financial domain experience mandatory.
• 3 years of cloud data warehouse skills such as Snowflake, Redshift, Databricks, or Bigquery.
• 3 years of cloud based data transformations tools such as dbt, matillion, or glue.
• Programming languages such as Python, SQL, Spark, or Java, with experience in data manipulation, transformation, and analysis.
• Expert level experience with cloud-based data platforms and services such as AWS, Snowflake or dbt.
• Database systems, data warehousing, data patterns/architectures, and SQL query optimizations.

CONTACT:

To apply, send resume to: Lalia Taylor at ltaylor@teampurpose.com. Please reference job title and location.