Offer summary

Qualifications:

5+ years of experience in a Data Engineer role, Graduate degree in Computer Science, Statistics, Informatics, Information Systems or a related field, Advanced SQL knowledge and experience with relational and NoSQL databases, Strong analytic skills and experience with big data architectures and data pipelines..

Key responsibilities:

Design and build data pipelines to ensure efficient data flow across the organization

Modernize data infrastructure by evolving the data platform and creating cohesive data models

Collaborate with cross-functional teams to translate data requirements into scalable solutions

Ensure data quality and performance by troubleshooting issues and refining data architectures.

Job description

Founded in 2017, REPS & Co. has rapidly become a leader in data analytics in the entertainment industry. Recognized on the Forbes list of America's Best Startup Employers, we focus on delivering advanced analytics that supports data driven decisions. Our solutions provide comprehensive insights and forecasts, enabling us to have a better understanding and response to supply and demand in the ticketing world. With a commitment to driving innovation, REPS & Co. helps shape a dynamic market environment.

We are seeking a highly motivated, self-starting Data Engineer with a strong sense of ownership and an insatiable desire to learn. In this individual contributor role, you will design, build, and optimize robust data pipelines and scalable architectures that drive our business forward. If you thrive in fast-paced environments, love solving complex problems, and enjoy exploring new technologies, you’ll fit right in with our team.

The ideal candidate will be responsible for:

Design & Build Data Pipelines: Develop, implement, and optimize ETL/ELT processes to ensure efficient and high-quality data flow across the organization
Modernize Data Infrastructure: Contribute to evolving our data platform—from unstructured environments to a streamlined, cohesive data model, including data warehouses and lakes
Collaborative Problem Solving: Work closely with cross-functional teams and business stakeholders to translate data requirements into scalable solutions
Data Quality & Performance: Ensure high standards for data accuracy, security, and performance by troubleshooting issues and refining data architectures
Continuous Learning & Innovation: Stay ahead of the curve by researching and adopting emerging technologies and best practices that enhance our data ecosystem
Agile Development Participation: Engage actively in agile development processes, contributing ideas and improvements that support team collaboration and efficiency

Qualifications:

Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
Experience building and optimizing ‘big data’ data pipelines, architectures and data sets
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
Strong analytic skills related to working with unstructured datasets
Build processes supporting data transformation, data structures, metadata, dependency and workload management
A successful history of manipulating, processing and extracting value from large disconnected datasets
Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores
Strong project management and organizational skills
Experience supporting and working with cross-functional teams in a dynamic environment
We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field

They should also have experience using the following software/tools:

Experience with relational SQL and NoSQL databases, including RDS, Postgres, MySQL, Mongo / DynamoDB, and Cassandra
Experience in data pipeline and workflow tools: DBT, Lambda, AirByte, Airflow, etc.
Experience with BigData cloud services: Snowflake, BigQuery, EMR, RDS, Redshift, Glue, Athena
Experience with stream-processing systems: Druid, Storm, Spark-Streaming, etc.
Experience with object-oriented languages: Python, Java, Javascript, etc.

Benefits