Ideally you have an in-depth understanding of streaming data technologies like Amazon Kinesis or Apache Kafka, and experience with open-source data processing frameworks like Apache Spark, Apache Flink, or Apache Storm.

Big Data & Streaming: 2+ years using big data and/or streaming technologies (e.g. Apache Spark, Apache Kafka, Apache Flink) Design, develop and deliver scalable, robust and highly re-usable components using technologies such as Python, Java, AWS serverless (Lambda, Glue), Apache Spark, Apache Kafka and REST.

4+ Experience with technologies Apache Mesos, Marathon, or Apache Spark. Utilize programming languages like Java, Python, SQL, Ruby and Go, Container Orchestration services including Docker and Kubernetes, CM tools including Ansible and Terraform, and a variety of AWS tools and services.

4+ experience with coding and scripting (Python, SQL, Java, JavaScript, Golang, Bash, Perl or Ruby) This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI.

At least 3 years of experience in Cloud Native technologies (Amazon Web Services, Microsoft Azure, Google Cloud Platform) At least 6 years of experience in DevOps Engineering (Internship experience does not apply.

New York City (Hybrid On-Site): $201,400 - $229,900 for Lead Software Engineer. 2+ Experience with distributed database systems (Cassandra, ElasticSearch) Lead a portfolio of diverse technology projects and a team of developers with deep experience in machine learning, distributed microservices, and full stack systems to create solutions that help meet regulatory needs for the company.

As a DevOps Engineer, you’ll have the opportunity to be on the forefront of driving a major transformation within Capital One. 4+ Experience using build and deployment tools (Jenkins, Docker) At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors, who love to solve real problems and meet real customer needs.

Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC.

Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law.

130 5th Ave (22130), United States of America, New York, New YorkLead Software Engineer, DevOps. Collaborate with digital product managers, and deliver robust cloud-based solutions that drive powerful experiences to help millions of Americans achieve financial empowerment.

At least 4 years of Unix or Linux system administration experience. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. We are seeking DevOps Engineers who are passionate about marrying data with emerging technologies to join our team.

Skills Minimum 8+ years in Adobe MarTech (Target, Analytics, Launch) and AEM and hands-on experience programming in Web Technologies like JSP, JavaScript, XML, XPATH, AJAX, jQuery, Adobe APIs, Apache Sling, OSGi bundles, Apache Web Server.

At this time, Capital One will not sponsor a new applicant for employment authorization for this position. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com.

Experience using workflow runners including Github Action Runners, Jenkins Agents, Apache Airflow Workers, and Apache Spark. 2) Expertise in System Design and Architecture: Assist in the design and architect cloud infrastructure solutions using Apache Spark for distributed data processing and analytics.

Knowledge of Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Hive (Apache), Informatica, Microsoft Azure, Microsoft Databricks, Microsoft Power BI, Microsoft SharePoint, Microsoft SQL Server, MS Office Products Operation Data Integration (OLTP) and Python.