Data Engineer II, SPIV Data Engineering

Technology, Data & Digital · Data, AI & Analytics · Data Engineering

In short

We are seeking an experienced Data Engineer to join our Selling Partner Identity Verification team. You will be responsible for designing, implementing, and maintaining data infrastructure and pipelines, working closely with cross-functional teams to deliver scalable data solutions. This role requires experience with data modeling, ETL, SQL, and scripting languages like Python, with preferred experience in AWS technologies.

Responsibilities

Lead the design and implementation of data pipelines for analytical and operational needs.
Design and develop scalable, high-performance data systems using modern data platforms.
Collaborate with data scientists, analysts, and stakeholders to understand data requirements.
Optimize data storage and retrieval systems for performance and cost-effectiveness.
Implement data quality checks and monitoring systems.
Mentor junior engineers and provide technical leadership.
Evaluate and recommend new technologies and tools.
Contribute to the development of data governance policies and procedures.
Troubleshoot and resolve complex data-related issues.

Requirements

3+ years of data engineering experience
Experience with data modeling, warehousing, and building ETL pipelines
Experience with SQL
Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS

Desired Qualifications

Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

Benefits

High value on work-life balance
Supportive environment for new members
Broad mix of experience levels and tenures
Environment that celebrates knowledge sharing and mentorship

Skills

SQLPythonJavaScalaNodeJSRedshiftS3AWS GlueEMRKinesisFireHoseLambdaIAM

#Data Engineer#Data Engineering#ETL#Data Modeling#AWS

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