Oliver James
Job Title: Data Engineer
Location: Malvern, PA (Hybrid - 2 days onsite)
Salary: $130,000 - $150,000
No Third Parties
We're looking for a technically skilled and mission-aligned Cloud Data Engineer to design and build the foundational elements of a next-generation business intelligence and analytics platform in a cloud-native environment.
You'll work alongside a senior architecture leader and collaborate closely with data science and analytics stakeholders to develop an enterprise-grade data lakehouse ecosystem. From building scalable pipelines to implementing data cataloging and layered data architecture, your work will directly support critical decision-making and data science initiatives in a high-impact setting.
Key Responsibilities: Architect and build robust, scalable ETL/ELT workflows (batch and real-time) using AWS-native services such as Glue, Lambda, DMS, AppFlow, and Step Functions. Develop a unified data lakehouse environment supporting both structured and semi-structured data across bronze, silver, and gold layers. Implement and manage a metadata catalog to improve data discovery, governance, and lineage tracking. Design and maintain performant data models that enable advanced analytics and machine learning. Collaborate with the data architecture team to ensure alignment with enterprise standards and best practices. Enable data science and analytics teams with well-curated datasets and optimized Tableau integrations. Continuously optimize data pipelines for efficiency, scalability, and cost-effectiveness. Document workflows, transformation logic, and dbt models to ensure platform transparency and maintainability. Stay current with developments in modern data stack technologies and advocate for improvements where beneficial. Skills Needed:
A bachelor's or master's degree in Computer Science, Engineering, or a related technical field. 5+ years of experience in data engineering, particularly in cloud environments (AWS preferred). Expertise in building cloud-native data architectures, with experience developing and managing data lakehouse platforms. Proficient in scripting and data wrangling with Python, SQL, and Bash. Hands-on experience with orchestration tools (e.g., Airflow, Step Functions) and CI/CD practices (e.g., Jenkins). Strong grasp of ETL/ELT workflow orchestration concepts, especially DAG-based systems. Experience with event-driven architecture and AWS messaging services like SNS, SQS, or EventBridge. Deep knowledge of file and table formats used in lakehouse environments (e.g., Parquet, Iceberg). Familiarity with both business and technical data catalog tools (e.g., Atlan, Data.World, AWS Glue, Snowflake Catalog). Experience supporting analytics and BI tooling, particularly Tableau. Understanding of governance frameworks, metadata management, and data quality practices. Proven ability to clearly communicate complex data topics to both technical and non-technical audiences. Experience in nonprofit, mission-driven, or social impact organizations is a plus.
Location: Malvern, PA (Hybrid - 2 days onsite)
Salary: $130,000 - $150,000
No Third Parties
We're looking for a technically skilled and mission-aligned Cloud Data Engineer to design and build the foundational elements of a next-generation business intelligence and analytics platform in a cloud-native environment.
You'll work alongside a senior architecture leader and collaborate closely with data science and analytics stakeholders to develop an enterprise-grade data lakehouse ecosystem. From building scalable pipelines to implementing data cataloging and layered data architecture, your work will directly support critical decision-making and data science initiatives in a high-impact setting.
Key Responsibilities: Architect and build robust, scalable ETL/ELT workflows (batch and real-time) using AWS-native services such as Glue, Lambda, DMS, AppFlow, and Step Functions. Develop a unified data lakehouse environment supporting both structured and semi-structured data across bronze, silver, and gold layers. Implement and manage a metadata catalog to improve data discovery, governance, and lineage tracking. Design and maintain performant data models that enable advanced analytics and machine learning. Collaborate with the data architecture team to ensure alignment with enterprise standards and best practices. Enable data science and analytics teams with well-curated datasets and optimized Tableau integrations. Continuously optimize data pipelines for efficiency, scalability, and cost-effectiveness. Document workflows, transformation logic, and dbt models to ensure platform transparency and maintainability. Stay current with developments in modern data stack technologies and advocate for improvements where beneficial. Skills Needed:
A bachelor's or master's degree in Computer Science, Engineering, or a related technical field. 5+ years of experience in data engineering, particularly in cloud environments (AWS preferred). Expertise in building cloud-native data architectures, with experience developing and managing data lakehouse platforms. Proficient in scripting and data wrangling with Python, SQL, and Bash. Hands-on experience with orchestration tools (e.g., Airflow, Step Functions) and CI/CD practices (e.g., Jenkins). Strong grasp of ETL/ELT workflow orchestration concepts, especially DAG-based systems. Experience with event-driven architecture and AWS messaging services like SNS, SQS, or EventBridge. Deep knowledge of file and table formats used in lakehouse environments (e.g., Parquet, Iceberg). Familiarity with both business and technical data catalog tools (e.g., Atlan, Data.World, AWS Glue, Snowflake Catalog). Experience supporting analytics and BI tooling, particularly Tableau. Understanding of governance frameworks, metadata management, and data quality practices. Proven ability to clearly communicate complex data topics to both technical and non-technical audiences. Experience in nonprofit, mission-driven, or social impact organizations is a plus.