Lead Data Engineer

Capital One Financial

Confirmed live 2 days ago Low trust

Quick summary

Work type: On-site
Location: Chicago, IL
Salary: $179,400–$204,700 / yr
Posted: 65 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $180k

This role $192k

$141k most similar roles pay here $225k

This role pays more than 57% of similar roles. Most pay $149,106–$211,200 — the shaded band above. At the midpoint, this role pays about $192k versus about $180k for comparable roles.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 998 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 992 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Lead Data Engineer

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As a Lead Data Engineer, you will join a collaborative team focused on building robust, large-scale data pipelines using massive datasets to drive intelligent customer acquisition campaigns. You will design, develop, test, and support technical solutions within an Agile environment while collaborating with developers experienced in machine learning and distributed microservices. Your daily work involves managing high-volume batch and digital data streams to solve complex big data challenges involving extreme volume and velocity. The role requires proficiency in Python, Spark, AWS, Databricks, Snowflake, and Airflow, along with experience in Java, Scala, SQL, and NoSQL databases like Mongo or Cassandra. You will also utilize interactive AI tools to accelerate your workflow while performing unit tests and code reviews to ensure high-performance results for critical business lines.

Skills

Python Spark AWS Databricks Snowflake Airflow Java Scala SQL Redshift NoSQL Kafka Hadoop Hive EMR MySQL Cassandra UNIX Linux Agile

What you'll do

Design, develop, test, and support technical solutions using full-stack development tools and technologies.
Build robust, large-scale data pipelines using Python, Spark, AWS, Databricks, Snowflake, and Airflow.
Manage high-volume batch and digital data streams to drive targeted customer acquisition campaigns.
Develop cloud-based solutions that integrate with machine learning, distributed microservices, and full-stack systems.
Perform unit tests and conduct peer code reviews to ensure performance tuning and high-quality coding standards.
Mentor other members of the engineering community and share knowledge on emerging technology trends.
Utilize advanced AI tools to accelerate development workflows and improve productivity.

What we're looking for

At least 4 years of experience in application development.
At least 2 years of experience in big data technologies.
At least 1 year of experience with cloud computing (AWS, Microsoft Azure, or Google Cloud).
Experience with programming languages including Python, SQL, Scala, and Java.
Experience with distributed data tools such as Spark, Hadoop, Hive, Kafka, or MapReduce.
Experience with data warehousing services like Redshift or Snowflake.
Experience with Agile engineering practices and interactive AI tooling to accelerate productivity.
Work authorization that require immigration support from an employer.

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