Sr. Data Modeler
POSITION SUMMARY:
The Sr. Data Engineer / Data Modeler is a hands-on technical role focused on full stack development within the Enterprise Data organization. The role will pay curtail part in shaping future big data and analytics initiatives.
PRINCIPAL RESPONSIBILITIES:
- Design and implement Medallion Architecture, dimensional models (Star/Snowflake schemas), and metadata-driven modeling approaches for enterprise data warehouses
- Develop canonical and semantic data models with effective SCD handling techniques that align with business requirements and analytical needs
- Write and optimize advanced SQL queries in Snowflake (or similar platforms) to ensure efficient data processing and warehouse performance
- Align data models with ELT/ETL pipelines and analytics frameworks to create scalable data structures that grow with business demands
- Designs and develops code and data pipelines to ingest from relational databases (Oracle, SQL Server, DB2, Aurora), file shares, and web services.
- Streaming ingestion with Kinesis Streams, Kinesis Firehose, Kinesis Analytics and Kafka(MSK)
- Build Data Lake on AWS S3 with optimal performance considerations by partitioning and compressing data.
- Data Engineering and Analytics using AWS Glue, Informatica, EMR, Spark, Athena, Python.
- Data modeling and building Data Warehouse using Snowflake.
- Designs and develops code and data pipelines to ingest relational databases, file shares, and web services.
- Participates in requirements definition, system architecture design, and data architecture design.
- Participates in all aspects of the software life cycle using Agile development methodologies.
QUALIFICATIONS:
- Experience adopting and championing AI-assisted development practices within a team, including establishing guardrails for responsible use, and coaching engineers to use AI assistance effectively without compromising code quality or security standards
- 5+ years’ experience with data modeling tools like sqlDBM, ERWIN, Lucid
- 7+ years of experience in Enterprise Information Solution Architecture, Design, and development required.
- 7+ years of experience with integration architectures such as SOA, Microservices, ETL or other integration technologies.
- 7+ years of experience with working content or knowledge management systems, search engines, relational databases, NoSQL databases, ETL tools, geospatial systems, or semantic technology.
- Experience adopting and championing AI-assisted development practices within a team, including establishing guardrails for responsible use, and coaching engineers to use AI assistance effectively without compromising code quality or security standards
- 5+ years of hands-on experience with AWS services ( S3, Kinesis, Lambda, Athena, Glue, EMR) required.
- 5+ years of analytics tools like SAS, R, Python, and other advanced statistical software.
- Experience with JSON or XML data modeling required.
- Experience with Git/GitHub, branching, and other modern source code management methodologies required.
- Domain knowledge of NoSQL or relational database required.
- Understanding of database architecture and performance implications required.
Experience with Machine Learning and Artificial Intelligence.
- Ability to multi-task effectively.
- Ability to work collaboratively as part of an Agile Team.
- Extensive knowledge and experience with Python, JavaScript and Java.
- Excellent written and verbal communication skills, sense of ownership, urgency and drive.
MINIMUM QUALITIFICATIONS:
- Bachelor’s degree in computer science, Computer Information Systems, Engineering, Statistics or closely related field (willing to accept foreign education equivalent) (required).
- Experience in AWS services for data and analytics (required).
- 5 years of experience in Data Ingestion, Data Extraction, and Data Integration (required).
The statements used herein are intended to describe the general nature and level of the work being