Senior Data Engineer

UST

$72K — $108K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 8-10 years of total experience in data engineering roles
  • Strong proficiency in Python and SQL; knowledge of Scala/Java a plus
  • Expertise in Apache Spark for both batch and streaming data processing
  • Experience with messaging queues like Apache Kafka or Google Pub/Sub
  • Familiarity with cloud services, particularly GCP and Azure
  • Understanding of data warehousing solutions, including Snowflake and Redshift
  • Knowledge of orchestration tools such as Airflow, and containerization technologies like Docker and Kubernetes

Responsibilities

  • Design and develop ETL/ELT pipelines for batch and real-time data processing
  • Optimize scalable data architectures, including data lakes and warehouses
  • Build data ingestion frameworks from diverse data sources
  • Implement real-time streaming solutions using Apache Kafka and Flink
  • Monitor and enhance streaming applications for throughput and reliability
  • Manage Kafka topics, partitions, and processing pipelines
  • Conduct performance tuning for Spark jobs and data processing workflows

Benefits

  • Accrue a minimum of 10 days of paid vacation per year
  • Receive 6 days of paid sick leave annually
  • Eligible for 10 paid holidays and bereavement leave
  • Participate in the 401(k) Retirement Plan with employer matching
  • Comprehensive health insurance options including medical, dental, and vision
  • Access to basic life insurance and disability benefits
  • Opportunity to contribute to Health Savings Account (HSA) and Flexible Spending Account (FSA)
Full Job Description
Role description

Senior Data Engineer

Lead I - Data Engineering

UST is searching for a Data Engineer with Spark & Streaming skills builds real-time, scalable data pipelines using tools like Spark, Kafka, and cloud services (GCP) to ingest, transform, and deliver data for analytics and ML.

The opportunity:
• As a Senior Data Engineer, you will Design, develop, and maintain ETL/ELT data pipelines for batch and real-time data ingestion, transformation, and loading using Spark (PySpark/Scala) and streaming technologies (Kafka, Flink).
• Build and optimize scalable data architectures, including data lakes, data warehouses (BigQuery), and streaming platforms.
• Design, develop, and maintain scalable ETL/ELT pipelines for batch and real-time data processing.
• Build data ingestion frameworks to collect data from multiple sources including databases, APIs, files, and streaming systems.
• Design and implement real-time streaming solutions using Apache Kafka and Apache Flink.
• Develop event-driven architectures for low-latency data processing and analytics.
• Monitor and optimize streaming applications for throughput, scalability, and reliability.
• Manage Kafka topics, partitions, consumer groups, and stream processing pipelines.
• Performance Tuning: Optimize Spark jobs, SQL queries, and data processing workflows for speed, efficiency, and cost-effectiveness
• Data Quality: Implement data quality checks, monitoring, and ing systems to ensure data accuracy and consistency.

This position description identifies the responsibilities and tasks typically associated with the performance of the position. Other relevant essential functions may be required.

What you need:
• Experience range : 8-10 Years
• Programming: Strong proficiency in Python, SQL, and potentially Scala/Java.
• Big Data: Expertise in Apache Spark (Spark SQL, DataFrames, Streaming).
• Streaming: Experience with messaging queues like Apache Kafka, or Pub/Sub.
• Cloud: Familiarity with GCP, Azure data services.
• Databases: Knowledge of data warehousing (Snowflake, Redshift) and NoSQL databases.
• Tools: Experience with Airflow, Databricks, Docker, Kubernetes is a plus.
• Experience and Skills:
• Minimum 8 years overall
• GCP - 4 + years of recent GCP experience
• Qualification:
• Bachelor's Degree in computer science or equivalent experience

Compensation can differ depending on factors including but not limited to the specific office location, role, skill set, education, and level of experience. UST provides a reasonable range of compensation for roles that may be hired in various U.S. markets as set forth below.

Role Location: Bentonville, Arkansas

Compensation Range: $72,000-$108,000

Benefits

Full-time, regular employees accrue a minimum of 10 days of paid vacation per year, receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year), 10 paid holidays, and are eligible for paid bereavement leave and jury duty. They are eligible to participate in the Company's 401(k) Retirement Plan with employer matching. They and their dependents residing in the US are eligible for medical, dental, and vision insurance, as well as the following Company-paid Employee Only benefits: basic life insurance, accidental death and disability insurance, and short- and long-term disability benefits. Regular employees may purchase additional voluntary short-term disability benefits, and participate in a Health Savings Account (HSA) as well as a Flexible Spending Account (FSA) for healthcare, dependent child care, and/or commuting expenses as allowable under IRS guidelines. Benefits offerings vary in Puerto Rico.

Part-time employees receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year) and are eligible to participate in the Company's 401(k) Retirement Plan with employer matching.

Full-time temporary employees receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year) and are eligible to participate in the Company's 401(k) program with employer matching. They and their dependents residing in the US are eligible for medical, dental, and vision insurance.

Part-time temporary employees receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year).

All US employees who work in a state or locality with more generous paid sick leave benefits than specified here will receive the benefit of those sick leave laws.

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