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Data Architect

2 months ago

Chicago Illinois, United States Tiger Analytics Full time
About the Role

Tiger Analytics is a leading advanced analytics consulting firm, renowned for its expertise in Data Science, Machine Learning, and AI. As a trusted partner to multiple Fortune 500 companies, we empower businesses to unlock value from their data. Our commitment to excellence has been recognized by market research firms like Forrester and Gartner.

Job Summary

We are seeking a highly skilled Data Engineer to join our team. The successful candidate will be responsible for designing, implementing, and maintaining advanced analytics capabilities. Key responsibilities include:

Data Integration
  • Implement and maintain data synchronization between on-premises Oracle databases and Snowflake using Kafka and CDC tools.
Data Modeling
  • Assist in developing and optimizing the data model for Snowflake, ensuring it supports our analytics and reporting requirements.
Data Pipeline Development
  • Design, build, and manage data pipelines for the ETL process, using Airflow for orchestration and Python for scripting, to transform raw data into a format suitable for our new Snowflake data model.
Reporting Support
  • Collaborate with data architect to ensure the data within Snowflake is structured in a way that supports efficient and insightful reporting.
Technical Documentation
  • Create and maintain comprehensive documentation of data pipelines, ETL processes, and data models to ensure best practices are followed and knowledge is shared within the team.
Requirements
  • 8+ years of overall industry experience specifically in data engineering.
  • 5+ years of experience building and deploying large-scale data processing pipelines in a production environment.
  • Strong experience in Python, SQL, and PySpark.
  • Creating and optimizing complex data processing and data transformation pipelines using Python.
  • Experience with Snowflake Cloud Datawarehouse and DBT tool.
  • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
  • Understanding of Datawarehouse (DWH) systems, and migration from DWH to data lakes/Snowflake.
  • Understanding of ELT and ETL patterns and when to use each. Understanding of data models and transforming data into the models.
  • Strong analytic skills related to working with unstructured datasets.
  • Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
What We Offer

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility. Join our team and be part of shaping the future of data analytics.