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