Lead Data Engineer, Finance Technology

Target

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Brooklyn Park, MN
Salary
$132,000–$238,000 / yr
Posted
28 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $179k
This role $185k
$119k most similar roles pay here $251k

This role pays less than 54% of similar roles. Most pay $147,775–$211,200 — the shaded band above. At the midpoint, this role pays about $185k versus about $179k for comparable roles.

Based on 240 similar postings.

Employer

About Target

Target Corporation is a large-format general merchandise and grocery retailer offering a wide assortment of everyday essentials, apparel, home goods, and electronics through stores and online. Industry: General Merchandise Retail

Target currently has 58 open roles on FindRole.

Listed pay typically runs $98,000–$176,000 across 58 roles with salary data.

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View all roles at Target

At a glance

TL;DR · Lead Data Engineer, Finance Technology

Lead Data Engineer - Finance Technology (Hadoop, PySpark, Scala/Java) serves as the technical lead for the Finance Technology team within Core Retail Services. In this role, you will architect and build scalable, high-performance data pipelines and distributed processing solutions to power the financial backbone of enterprise operations, including accounts payable, treasury, and core accounting. You will design real-time and batch data processing systems, develop APIs for low-latency access, and optimize data models for efficiency. The role requires expertise in Hadoop, Spark, PySpark, Scala, and Java, along with experience in cloud platforms like AWS, GCP, or Azure, and tools such as Databricks, Snowflake, Kafka, and Flink. You will solve complex problems regarding financial reporting by integrating various data domains to provide near real-time insights for critical business decision-making across the organization.

What you'll do

  • Architect and build scalable data pipelines using Spark, Scala, Java, and cloud platforms like AWS, GCP, or Azure.
  • Design and implement real-time and batch data processing solutions for analytical and operational use.
  • Develop APIs and data services to provide low-latency, high-throughput access to data for downstream applications.
  • Optimize data models, workflows, and processing frameworks to improve performance, scalability, and cost efficiency.
  • Drive data governance, security, and compliance best practices across large-scale data environments.
  • Provide technical leadership and mentor engineers to foster engineering excellence and best practices.
  • Collaborate with product teams and stakeholders to translate business requirements into technical data solutions.

What we're looking for

  • A BS or MS in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, or a related technical field is preferred.
  • Candidates should have 7 plus years of experience in data engineering, software development, or distributed systems.
  • Expertise is required in Big Data technologies including Hadoop and Spark.
  • Strong programming skills are required in PySpark, Scala, and/or Java.
  • Experience with cloud platforms (AWS, GCP, or Azure) and associated services like S3, BigQuery, Databricks, EMR, or Snowflake is required.
  • Proficiency in API development using REST, GraphQL, or gRPC is required.
  • Experience with real-time and streaming data architectures such as Kafka, Flink, or Kinesis is required.
  • Knowledge of data modeling, ETL pipeline design, performance optimization, and data governance is required.

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