18 Data Engineer II Jobs in Arlington, TX
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GM Financial is Hiring a Data Engineer II Near Arlington, TX
ResponsibilitiesWe seek a Data Engineer who brings a robust skill set and extensive experience in cloud-based data engineering experience particularly within the realm of Azure and Databricks using Python, PySpark and cloud SQL. Critical thinking and problem-solving abilities are paramount, as you will navigate evolving and complex requirements and collaborate with stakeholders across diverse technical backgrounds. Your primary focus will revolve around data engineering development tasks, serving as a visionary alongside Data Engineering leads to refine and expand reusable libraries and common framework, ensuring it can accommodate the growing volume of incoming projects. You will also engage into engineering tasks, such as constructing pipelines and deployments that bolster various programs, projects, and initiatives supporting multiple customer needs.
What makes you an ideal candidate?
- Work closely with data scientists, data architects, developers, other IT counterparts, and business partners to identify, capture, collect and format data from the external sources, internal systems, and the data warehouse to extract features of interest.
- Designing and implementing internal process improvements including pipeline redesigns for greater scalability, optimizing data delivery, and automating manual processes.
- Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using Azure and Databricks technologies
- Experience with ingesting various source data formats such as JSON, Parquet, SequenceFile, Cloud Databases, MQ, No SQL, flat files, Event Hubs and Relational Databases such as Oracle
- Experience with Cloud technologies (such as Azure, AWS, GCP) and native toolsets such as Azure ARM Templates, Hashicorp Terraform, AWS Cloud Formation
- Thorough understanding of Hybrid Cloud Computing: virtualization technologies, Infrastructure as a Service, Platform as a Service and Software as a Service Cloud delivery models and the current competitive landscape
- Working knowledge of Object Storage technologies to include but not limited to Data Lake Storage Gen2, Delta Lake, S3, Minio, Ceph, ADLS
- Working knowledge of NoSQL data stores such as CosmosDB, MongoDB, Cassandra, Redis, Riak or other technologies that embed NoSQL with search such as MarkLogic or Lily Enterprise
- Working knowledge with containerization to include but not limited to Dockers, Kubernetes, Spark on Kubernetes, Spark Operator
- Proficient in SQL and Python, with the ability to utilize these tools effectively
- Seasoned in refining and enhancing existing data pipelines to unlock peak efficiency and exceptional performance
- Self-motivated problem solver with a keen eye for identifying and rectifying data inaccuracies
- Collaborative mindset, thriving in cross-functional teams by effectively sharing knowledge and contributing to the delivery of high-quality products
- Collaborate with the team to identify opportunities for innovation and improvement, actively contributing to the continuous evolution of our data infrastructure and engineering capabilities
- Working knowledge of Agile development /SAFe, Scrum and Agile Software Development methodologies
- Ability to thrive in an Agile/Scrum team environment
- Background with source control management systems (GIT or Subversion); Build Systems (Maven, Gradle, Webpack); Code Quality (Sonar); Artifact Repository Managers (Artifactory), Continuous Integration/ Continuous Deployment (Azure DevOps)
- SQL experience: querying data and sharing what insights can be derived
- Understanding of cloud solutions such as Google Cloud Platform, Microsoft Azure & Amazon AWS cloud architecture & services
- Knowledgeable of best practices in information technology governance, privacy, compliance and security topics
- Bachelor’s Degree in related field or equivalent work experience required
- 4-6 years of hands-on experience with data engineering required
- 3-5 years of hands-on experience with processing large data sets required
- 3-5 years of hands-on experience with SQL, data modeling, relational databases and/or no SQL databases required
Our Culture: Our team members define and shape our culture — an environment that welcomes innovative ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work — we thrive.
Compensation: Competitive pay and bonus eligibility
Work Life Balance: Flexible hybrid work environment, 2-days a week in office
Note:Please note we are not able to consider candidates who require visa sponsorship for this position.
Job Summary
Full Time
Investment Management
$86k-109k (estimate)
07/21/2023
07/04/2024
gmfinancial.com
AUSTIN, TX
7,500 - 15,000
1992
Public
ANGELA I GARDNER
$10B - $50B
Investment Management
Related Companies
About GM Financial
GM Financial is a financial services firm that provides commercial lending and auto financing solutions for individuals and businesses.
The job skills required for Data Engineer II include Python, Data Engineering, Data Warehouse, Java, Machine Learning, Data Science, etc. Having related job skills and expertise will give you an advantage when applying to be a Data Engineer II. That makes you unique and can impact how much salary you can get paid. Below are job openings related to skills required by Data Engineer II. Select any job title you are interested in and start to search job requirements.
The following is the career advancement route for Data Engineer II positions, which can be used as a reference in future career path planning. As a Data Engineer II, it can be promoted into senior positions as a Database Engineer III that are expected to handle more key tasks, people in this role will get a higher salary paid than an ordinary Data Engineer II. You can explore the career advancement for a Data Engineer II below and select your interested title to get hiring information.
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