Fidelity Corp
Data Engineer
Works closely with the business units and architects to gather requirements, plan, design, develop and deploy on-premises and cloud-based applications. Writes SQL queries in Oracle/Snowflake and performs performance optimization for large datasets. Develops ETL/ELT pipelines to move data to and from Snowflake data store using Python, AWS and Snowflake. Primary Responsibilities: Analyzes business requirements and delineates possible roadmaps and milestone plans to achieve the desired strategic initiatives. Collaborates with various business units to fulfill their needs as well as their customer's, provides technical support such as application and framework development and data management solution and implementation. Develops ingestion and transformation frameworks to establish data pipelines that can collect logs and enable metadata for the consumption layer. Provides exploratory analysis and framework development, product development and enhancements, and platform and infrastructure solutions and support. Delivers actionable insights to various business units by way of data convergence, establishes lower costs for innovation. Education and Experience: Bachelor's degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and five (5) years of experience as a Principal, Data Engineer (or closely related occupation) building source for finance data lakes to support reporting and analytical needs using Allocation Rendering Tool (ART) /Anaplan/Snowflake and Python. Or, alternatively, Master's degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and three (3) years of experience as a Principal, Data Engineer (or closely related occupation) building source for finance data lakes to support reporting and analytical needs using Allocation Rendering Tool (ART) /Anaplan/Snowflake and Python. Skills and Knowledge: Candidate must also possess: Demonstrated Expertise ("DE") designing and developing Oracle database applications that processes Flat Files using shell scripts; and utilizes Informatica Workflows, database objects stored procedures, Informatica Power Center, and SQL Developer for data processing. DE performing development within the software development lifecycles using Informatica Power Center, Oracle, Netezza, Microsoft SQL Server, and Unix Shell scripting; and moving data across database using iSQL. DE designing and developing highly scalable Cloud data warehouses using Cloud computing tools -- Amazon Web Services (AWS) (EMR, S3, CloudFormation), pyspark and Apache NiFi -- and private Computing tools (Hive, Sqoop and HDFS). DE developing Python-based data ingestion applications to load structured data from relational databases and Anaplan APIs into a Cloud SaaS based Data Lake Platform using Snowflake, Amazon Web Services (AWS) (Lambda, S3, or EC2), Jenkins, GitHub, AtScale, Power BI, and Control-M.
Works closely with the business units and architects to gather requirements, plan, design, develop and deploy on-premises and cloud-based applications. Writes SQL queries in Oracle/Snowflake and performs performance optimization for large datasets. Develops ETL/ELT pipelines to move data to and from Snowflake data store using Python, AWS and Snowflake. Primary Responsibilities: Analyzes business requirements and delineates possible roadmaps and milestone plans to achieve the desired strategic initiatives. Collaborates with various business units to fulfill their needs as well as their customer's, provides technical support such as application and framework development and data management solution and implementation. Develops ingestion and transformation frameworks to establish data pipelines that can collect logs and enable metadata for the consumption layer. Provides exploratory analysis and framework development, product development and enhancements, and platform and infrastructure solutions and support. Delivers actionable insights to various business units by way of data convergence, establishes lower costs for innovation. Education and Experience: Bachelor's degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and five (5) years of experience as a Principal, Data Engineer (or closely related occupation) building source for finance data lakes to support reporting and analytical needs using Allocation Rendering Tool (ART) /Anaplan/Snowflake and Python. Or, alternatively, Master's degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and three (3) years of experience as a Principal, Data Engineer (or closely related occupation) building source for finance data lakes to support reporting and analytical needs using Allocation Rendering Tool (ART) /Anaplan/Snowflake and Python. Skills and Knowledge: Candidate must also possess: Demonstrated Expertise ("DE") designing and developing Oracle database applications that processes Flat Files using shell scripts; and utilizes Informatica Workflows, database objects stored procedures, Informatica Power Center, and SQL Developer for data processing. DE performing development within the software development lifecycles using Informatica Power Center, Oracle, Netezza, Microsoft SQL Server, and Unix Shell scripting; and moving data across database using iSQL. DE designing and developing highly scalable Cloud data warehouses using Cloud computing tools -- Amazon Web Services (AWS) (EMR, S3, CloudFormation), pyspark and Apache NiFi -- and private Computing tools (Hive, Sqoop and HDFS). DE developing Python-based data ingestion applications to load structured data from relational databases and Anaplan APIs into a Cloud SaaS based Data Lake Platform using Snowflake, Amazon Web Services (AWS) (Lambda, S3, or EC2), Jenkins, GitHub, AtScale, Power BI, and Control-M.