Data Engineer - Snowflake

Tiger Analytics; Chicago (IL); On-site; USD 63,000 - 117,200; Full time

Benefits offered by this job

Significant career development

Job summary

A leading analytics consulting firm is looking for an experienced Data Engineer in Chicago, IL. The ideal candidate will have over 8 years of experience in data engineering, expertise in Python, and a strong background in Snowflake and data modeling. Responsibilities include designing data pipelines and ensuring synchronization between databases. The role offers significant career development opportunities and the chance to contribute to important projects.

Qualifications

• Implement and maintain data synchronization between on-premises Oracle databases and Snowflake.
• Assist in optimizing the data model for Snowflake.
• Design, build, and manage data pipelines for ETL processes.
• Create and maintain documentation of data pipelines and ETL processes.

Responsibilities

• Collaborate with data architect for reporting structure in Snowflake.
• Utilize CI/CD tools for data pipeline automation.
• Work independently and solve complex problems.

Skills

Data Pipeline Development

Python

SQL

Data Integration

Data Modeling

Education

8+ years of industry experience in data engineering

5+ years building large-scale data processing pipelines

Tools

Snowflake

Airflow

Kafka

Databricks

DBT tool

Job description

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Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

The Data Engineer will be responsible for architecting, designing, and implementing advanced analytics capabilities. The right candidate will have broad skills in database design, be comfortable dealing with large and complex data sets, have experience building self-service dashboards, be comfortable using visualization tools, and be able to apply your skills to generate insights that help solve business challenges.We are looking for someone who can bring their vision to the table and implement positive change in taking the company's data analytics to the next level.

Requirements

Key Responsibilities:

Data Integration:

Implement and maintain data synchronization between on-premises Oracle databases and Snowflake using Kafka and CDC tools.

Support 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.

Tools and Skillsets:

Data engineering: proven track record of developing and maintaining data pipelines and data integration projects

Databases: Strong experience with Oracle, Snowflake, and Databricks.

Data Integration Tools: Proficiency in using Kafka and CDC tools for data ingestion and synchronization.

Orchestration Tools: Expertise in Airflow for managing data pipeline workflows.

Programming: Advanced proficiency in Python and SQL for data processing tasks.

Data Modeling: Understanding of data modeling principles and experience with data warehousing solutions.

Cloud Platforms: Knowledge of cloud infrastructure and services, preferably Azure, as it relates to Snowflake and Databricks integration.

Collaboration Tools: Experience with version control systems (like Git) and collaboration platforms.

CI/CD Implementation: Utilize CI/CD tools to automate the deployment of data pipelines and infrastructure changes, ensuring high-quality data processing with minimal manual intervention.

Communication: Excellent communication and teamwork skills, with a detail-oriented mindset. Strong analytical skills, with the ability to work independently and solve complex problems.

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 Data warehouse" 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
  
  

Benefits

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.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  IT Services and IT Consulting

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