Our vision is to transform how the world uses information to enrich life. Join an inclusive team passionate about one thing : using their expertise in the relentless pursuit of innovation for customers and partners.
The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible.
We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing.
Responsibilities and Tasks
Understand the Business Problem and the Relevant Data
Maintain an intimate understanding of company and department strategy
Translate analysis requirements into data requirements
Identify and understand the data sources that are relevant to the business problem
Develop conceptual models that capture the relationships within the data
Define the data-quality objectives for the solution
Be a subject matter expert in data sources and reporting options
Architect Data Management Systems
Use understanding of the business problem and the nature of the data to select appropriate data management system (Big Data, OLTP, OLAP, etc.)
Design and implement optimum data structures in the appropriate data management system (Hadoop, Teradata, SQL Server, etc.
to satisfy the data requirements
Plan methods for archiving / deletion of information
Develop, Automate, and Orchestrate an Ecosystem of ETL Processes for Varying Volumes of Data
Identify and select the optimum methods of access for each data source (real-time / streaming, delayed, static)
Determine transformation requirements and develop processes to bring structured and unstructured data from the source to a new physical data model
Develop processes to efficiently load the transform data into the data management system
Prepare Data to Meet Analysis Requirements
Work with the data scientist to implement strategies for cleaning and preparing data for analysis (e.g., outliers, missing data, etc.)
Develop and code data extracts
Follow standard methodologies to ensure data quality and data integrity
Ensure that the data is fit to use for data science applications
Qualifications and Experience :
4-7 years of experience developing, delivering, and / or supporting data engineering, advanced analytics or business intelligence solutions
Ability to work with multiple operating systems (e.g., MS Office, Unix, Linux, etc.)
Experienced in developing ETL / ELT processes using Apache Ni-Fi and Snowflake
Significant experience with big data processing and / or developing applications and data sources via Hadoop, Yarn, Hive, Pig, Sqoop, MapReduce, HBASE, Flume, etc.
Understanding of how distributed systems work
Familiarity with software architecture (data structures, data schemas, etc.)
Strong working knowledge of databases (Oracle, MSSQL, etc.) including SQL and NoSQL.
Strong mathematics background, analytical, problem solving, and organizational skills
Strong communication skills (written, verbal and presentation)
Experience working in a global, multi-functional environment
Minimum of 2 years’ experience in any of the following : At least one high-level client, object-oriented language (e.g.
one or more Data Extraction Tools (SSIS, Informatica etc.)
Ability to travel as needed
B.S. degree in Computer Science, Software Engineering, Electrical Engineering, Applied Mathematics or related field of study.
M.S. degree preferred.