Educational

• Background in programming, databases and/or big data technologies OR
BS/MS in software engineering, computer science, economics or other engineering fields

Responsibility

• Partner with Data Architect and Data Integration Engineer to enhance/maintain optimal data pipeline architecture aligned to published standards
• Assemble medium, complex data sets that meet functional /non-functional business requirements
• Design and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction transformation, and loading of data from a wide variety of data sources ‘big data’ technologies
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics
• Work with stakeholders including Domain leads, and Teams to assist with data-related technical issues and support their data infrastructure needs
• Ensure technology footprint adheres to data security policies and procedures related to encryption, obfuscation and role based access
Create data tools for analytics and data scientist team members

Functional Competency

• Knowledge of data and analytics framework supporting data lakes, warehouses, marts, reporting, etc
• Defining data retention policies, monitoring performance and advising any necessary infrastructure changes based on functional and non-functional requirements
• In depth knowledge of data engineering discipline
• Extensive experience working with Big Data tools and building data solutions for advanced analytics
• Minimum of 5+ years' hands-on experience with a strong data background
• Solid programming skills in Java, Python and SQL
• Clear hands-on experience with database systems - Hadoop ecosystem, Cloud technologies (e.g. AWS, Azure, Google), in-memory database systems (e.g. HANA, Hazel cast, etc) and other database systems - traditional RDBMS (e.g. Teradata, SQL Server, Oracle), and NoSQL databases (e.g. Cassandra, MongoDB, DynamoDB)
• Practical knowledge across data extraction and transformation tools - traditional ETL tools (e.g. Informatica, Ab Initio, Altryx) as well as more recent big data tools

Educational

• Background in programming, databases and/or big data technologies OR
BS/MS in software engineering, computer science, economics or other engineering fields

Responsibility

• Partner with Data Architect and Data Integration Engineer to enhance/maintain optimal data pipeline architecture aligned to published standards
• Assemble medium, complex data sets that meet functional /non-functional business requirements
• Design and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction transformation, and loading of data from a wide variety of data sources ‘big data’ technologies
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics
• Work with stakeholders including Domain leads, and Teams to assist with data-related technical issues and support their data infrastructure needs
• Ensure technology footprint adheres to data security policies and procedures related to encryption, obfuscation and role based access
Create data tools for analytics and data scientist team members

Functional Competency

• Knowledge of data and analytics framework supporting data lakes, warehouses, marts, reporting, etc
• Defining data retention policies, monitoring performance and advising any necessary infrastructure changes based on functional and non-functional requirements
• In depth knowledge of data engineering discipline
• Extensive experience working with Big Data tools and building data solutions for advanced analytics
• Minimum of 5+ years' hands-on experience with a strong data background
• Solid programming skills in Java, Python and SQL
• Clear hands-on experience with database systems - Hadoop ecosystem, Cloud technologies (e.g. AWS, Azure, Google), in-memory database systems (e.g. HANA, Hazel cast, etc) and other database systems - traditional RDBMS (e.g. Teradata, SQL Server, Oracle), and NoSQL databases (e.g. Cassandra, MongoDB, DynamoDB)
• Practical knowledge across data extraction and transformation tools - traditional ETL tools (e.g. Informatica, Ab Initio, Altryx) as well as more recent big data tools