Data Engineer

Gemini; New York (NY); Hybrid; USD 104,000 - 145,000; Full time

Benefits offered by this job

Health plans

401K with company matching

Paid Parental Leave

Flexible time off

Discretionary annual bonus

New hire equity grant

Job summary

Gemini is seeking a Data Engineer to design and deliver scalable data pipelines, dimensional models, and robust ETL processes. You will work with analysts and engineers to understand data needs, validate data quality, and implement production-grade solutions.

The role emphasizes collaboration across teams and a strong engineering mindset within a hybrid US-based environment. The team values data-driven decision making, reliable data infrastructure, and clear communication of insights to

Qualifications

• 4+ years experience in data engineering with data warehouse technologies.
• 4+ years experience in custom ETL design, implementation and maintenance.
• 4+ years experience with schema design and dimensional data modeling.
• Advanced skills with Python and SQL are a must.
• Experience with one or more MPP databases (Redshift, BigQuery, Snowflake, etc).
• Experience with one or more ETL tools (Informatica, Pentaho, SSIS, Alooma, etc).
• Strong computer science fundamentals including data structures and algorithms.
• Strong software engineering skills in any server side language, preferably Python.
• Experienced in working collaboratively across different teams and departments.
• Strong technical and business communication

Responsibilities

• Design, automate, build, and launch scalable, efficient and reliable data pipelines into production using Python
• Design, build and enhance dimensional models for Data Warehouse and BI solutions
• Research new tools and technologies to improve existing processes
• Work closely with data analysts to understand data integration and modeling requirements
• Develop new systems and tools to enable the teams to consume and understand data more intuitively
• Perform root cause analysis and resolve production and data issues
• Create test plans, test scripts and perform data validation
• Tune SQL queries, reports and ETL pipelines
• Build and maintain data dictionary and process documentation
• Take ownership and can work autonomously

Skills

Python

SQL

Data warehousing

ETL

Tools

Informatica

Pentaho

SSIS

Alooma

Redshift

BigQuery

Snowflake

Job description

About the CompanyGemini is a global crypto and Web3 platform founded by Tyler Winklevoss and Cameron Winklevoss in 2014. Gemini offers a wide range of crypto products and services for individuals and institutions in over 70 countries.Crypto is about giving you greater choice, independence, and opportunity. We are here to help you on your journey. We build crypto products that are simple, elegant, and secure. Whether you are an individual or an institution, we help you buy, sell, and store your bitcoin and cryptocurrency.At Gemini, our mission is to unlock the next era of financial, creative, and personal freedom.The Department: DataThe Role: Data EngineerAs a member of our data engineering team, you’ll shape the way we approach data at Gemini by using your engineering, analytical and communication skills to work with teams across the business. You know how to ask the right questions and are passionate about using data to support and drive informed business decisions. You are ready to roll up your sleeves and are excited to take on challenging opportunities and projects. You’ll mentor data engineers and analysts and guide our internal teams to use data to improve the product and achieve KPIs. Communicating your insights with leaders across the organization is paramount to success.Responsibilities:- Design, automate, build, and launch scalable, efficient and reliable data pipelines into production using Python- Design, build and enhance dimensional models for Data Warehouse and BI solutions- Research new tools and technologies to improve existing processes- Work closely with data analysts to understand data integration and modeling requirements- Develop new systems and tools to enable the teams to consume and understand data more intuitively- Perform root cause analysis and resolve production and data issues- Create test plans, test scripts and perform data validation- Tune SQL queries, reports and ETL pipelines- Build and maintain data dictionary and process documentation- Take ownership and can work autonomouslyMinimum Qualifications:- 4+ years experience in data engineering with data warehouse technologies- 4+ years experience in custom ETL design, implementation and maintenance- 4+ years experience with schema design and dimensional data modeling- Advanced skills with Python and SQL are a must- Experience with one or more MPP databases(Redshift, Bigquery, Snowflake, etc)- Experience with one or more ETL tools(Informatica, Pentaho, SSIS, Alooma, etc)- Strong computer science fundamentals including data structures and algorithms- Strong software engineering skills in any server side language, preferable Python- Experienced in working collaboratively across different teams and departments- Strong technical and business communicationPreferred Qualifications:- Kafka, HDFS, Hive, Cloud computing experience is a plus- Experience with Continuous integration and deployment- Knowledge and experience of financial markets, banking or exchangesIt Pays to Work HereThe compensation & benefits package for this role includes:- Competitive starting salary- A discretionary annual bonus- Long-term incentive in the form of a new hire equity grant- Comprehensive health plans- 401K with company matching- Paid Parental Leave- Flexible time offSalary Range: The base salary range for this role is between $104,000 - $145,000 in the State of New York, the State of California and the State of Washington. This range is not inclusive of our discretionary bonus or equity package. When determining a candidate’s compensation, we consider a number of factors including skillset, experience, job scope, and current market data.In the United States, we have a flexible hybrid work policy for employees who live within 30 miles of our office headquartered in New York City and our office in Seattle. Employees within the New York and Seattle metropolitan areas are expected to work from the designated office twice a week, unless there is a job‑specific requirement to be in the office every workday. Employees outside of these areas are considered part of our remote‑first workforce. We believe our hybrid approach for those near our NYC and Seattle offices increases productivity through more in‑person collaboration where possible.

Responsibilities

• Design, automate, build, and launch scalable, efficient and reliable data pipelines into production using Python
• Design, build and enhance dimensional models for Data Warehouse and BI solutions
• Research new tools and technologies to improve existing processes
• Work closely with data analysts to understand data integration and modeling requirements
• Develop new systems and tools to enable the teams to consume and understand data more intuitively
• Perform root cause analysis and resolve production and data issues
• Create test plans, test scripts and perform data validation
• Tune SQL queries, reports and ETL pipelines
• Build and maintain data dictionary and process documentation
• Take ownership and can work autonomously

Requirements

• 4+ years experience in data engineering with data warehouse technologies
• 4+ years experience in custom ETL design, implementation and maintenance
• 4+ years experience with schema design and dimensional data modeling
• Advanced skills with Python and SQL are a must
• Experience with one or more MPP databases(Redshift, Bigquery, Snowflake, etc)
• Experience with one or more ETL tools(Informatica, Pentaho, SSIS, Alooma, etc)
• Strong computer science fundamentals including data structures and algorithms
• Strong software engineering skills in any server side language, preferable Python
• Experienced in working collaboratively across different teams and departments
• Strong technical and business communication

Tech stack

• ETL
• Python
• Databases
• etl pipelines
• SQL
• Data