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Data Engineer Gcp Data Engineer Jobs in Delaware

Lead Data Engineer (Bank Tech)

Wilmington, DE · On-site

$99K - $131K/yr

Lead Data Engineer (Bank Tech) Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative ...

... data engineer. * Advanced knowledge of the Hadoop ecosystem and its components. * In-depth knowledge of Hive, HBase, and Pig. * Familiarity with MapReduce and Pig Latin Scripts. * Knowledge of ...

Lead Data Engineer | Onsite - Delaware

Wilmington, DE · On-site

$111K - $133K/yr

Must-Have Qualifications * 8+ years in data engineering, with 3+ years as a tech lead owning end-to-end delivery (not a pure design/review architect role). * Proven track record of shipping data ...

Lead Data Engineer | Onsite - Delaware

Wilmington, DE · On-site

$111K - $133K/yr

Must-Have Qualifications * 8+ years in data engineering, with 3+ years as a tech lead owning end-to-end delivery (not a pure design/review architect role). * Proven track record of shipping data ...

We are seeking an experienced Data Governance & Quality Engineer to play a key role in shaping Agilent's modern data management landscape. In this role, you will combine data governance, metadata ...

We are seeking an experienced Data Governance & Quality Engineer to play a key role in shaping Agilent's modern data management landscape. In this role, you will combine data governance, metadata ...

Bachelor's degree in Data Science, Computer Science, Data Engineering, Bioinformatics, Biochemistry, Biotechnology, Engineering or a related field. * At least five years of experience in data science ...

Showing results 21-40

Data Engineer Gcp Data Engineer information

What is the difference between Data Engineer Gcp Data Engineer vs Data Engineer?

AspectData Engineer Gcp Data EngineerData Engineer
CertificationsGCP certifications (e.g., Professional Data Engineer)Varies; often includes cloud or database certifications
Work EnvironmentPrimarily cloud-based, focusing on Google Cloud Platform toolsCan be cloud, on-premises, or hybrid environments
Industry UsageCommon in organizations leveraging Google Cloud servicesWidespread across industries using various cloud providers
Skills FocusGCP tools, BigQuery, Dataflow, Pub/SubSQL, ETL, data modeling, general cloud skills

In summary, Data Engineer Gcp Data Engineer specializes in Google Cloud Platform tools and certifications, focusing on cloud-native data solutions. Data Engineer is a broader role that may work across multiple platforms and environments, with a wider range of tools and technologies.

What are some common challenges faced by data engineers working with GCP, and how can they be addressed?

Data Engineers working with Google Cloud Platform (GCP) often encounter challenges such as optimizing data pipeline performance, managing costs, and ensuring data security and compliance. Effective use of GCP's native monitoring and logging tools can help identify bottlenecks in ETL processes, while leveraging features like autoscaling in Dataflow or BigQuery partitioning improves efficiency. Regular collaboration with DevOps and security teams is crucial to maintain robust cloud architecture and compliance with data regulations. Staying updated with GCP releases and best practices will also help proactively address evolving challenges.

What are the key skills and qualifications needed to thrive as a GCP data engineer?

To thrive as a GCP Data Engineer, you need strong expertise in data modeling, ETL processes, and cloud architecture, typically backed by a degree in computer science or related field. Proficiency with Google Cloud Platform services (like BigQuery, Dataflow, and Pub/Sub), SQL, and tools such as Python or Java is essential, and certifications like Google Professional Data Engineer are highly valued. Strong problem-solving, communication, and teamwork skills help you collaborate effectively and translate business needs into technical solutions. These abilities ensure efficient, scalable data pipelines and reliable infrastructure, which are critical for driving data-driven decision-making.

What is a GCP data engineer?

A GCP Data Engineer is a data engineering professional who specializes in designing, building, and managing data processing systems on Google Cloud Platform (GCP). They work with cloud-based tools and services to collect, transform, and analyze large volumes of data, enabling organizations to gain insights and make data-driven decisions. GCP Data Engineers are proficient in technologies such as BigQuery, Dataflow, Pub/Sub, and Cloud Storage. Their role often involves ensuring data pipelines are reliable, scalable, and secure while optimizing performance and cost.

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For Data Engineer Gcp Data Engineer jobs in Delaware, the most frequently searched job titles are:

What job categories do people searching Data Engineer Gcp Data Engineer jobs in Delaware look for?

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What cities in Delaware are hiring for Data Engineer Gcp Data Engineer jobs?

Cities in Delaware with the most Data Engineer Gcp Data Engineer job openings:

Infographic showing various Data Engineer Gcp Data Engineer job openings in Delaware as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior Data Engineer - Credit Data Analytics

MDAEdge

Wilmington, DE • On-site

$102K - $139K/yr

Full-time

Re-posted 27 days ago


Job description

Job Summary:
MDAEdge is a company that focuses on data-driven solutions, and they are seeking a Senior Data Engineer to drive data engineering efforts for enterprise-wide capabilities. The role involves developing analytics and automation solutions, managing complex data sets, and collaborating with various teams to enable data-informed decision making.
Responsibilities:
• The Corporate Audit and Credit Review (CACR) analytics & automation team delivers data-driven, risk-based insights and automation solutions to the CACR organization. The Senior Data Engineer role will be responsible for developing and implement a range of analytics and automation solutions, including data extraction, analysis, reporting, and dashboard design, but could include more advanced analytics including statistical analysis, text mining & NLP, and modeling/machine learning/AI. This role demands interaction with highly experienced audit and/or credit professionals, data experts and technology. Intellectual curiosity will drive critical thinking to produce optimal solutions. Strong time management, coordination, communication, and presentation skills are a must in this role.
• Assembles large, complex data sets that meet functional and non-functional requirements, ensuring that the design and engineering approach is consistent across multiple systems.
• Maintains, improves, cleans, and manipulates large data for operational and analytics data systems, builds complex processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management, and communicates required information for deployment, maintenance, and support of business functionality.
• Utilizes multiple architectural components in the design and development of client requirements and collaborates with development teams to understand data requirements and ensure the data architecture is feasible to implement.
• Defines and builds data pipelines to enable data-informed decision making, ensuring adherence to release processes and risk management routines
• Contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies any test issues and errors, and leads triage of underlying causes.
• Leads the identification of gaps in data management standards adherence and works with appropriate partners to develop plans to close gaps, leading concept testing and conducting research to prototype toolsets and improve existing processes.
• Mentors Data Engineers in the delivery and release of continuous integration and continuous delivery events and defines key performance indicators and internal controls.
• Utilizes sound, seasoned analytical skills to independently develop analytics & automated testing solutions using a variety of tools (Alteryx, Tableau, etc.) and programming languages (SQL, SAS, Python, etc.)
• Supports the design and execution of new analytics, automated testing tools, and models.
• Responsible for multiple projects simultaneously, ensuring each one is completed on time and efficiently with a high standard of work.
• Coordinates, schedules, scopes, and leads large, cross-functional analytics & automation activities.
• Exercises judgment, critical thinking, and sound communication skills to influence business partners.
• Coaches/trains junior team members in execution of analytics and automation activities.
• This position may also have responsibilities for managing associates. Here all managers at this level demonstrate the following responsibilities, in addition to those specific to the role, listed above.
• Diversity & Inclusion Champion: Models an inclusive environment for employees and clients, aligned to company D&I goals.
• Manager of Process & Data: Demonstrates deep process knowledge, operational excellence and innovation through a focus on simplicity, data-based decision making and continuous improvement.
• Enterprise Advocate & Communicator: Communicates enterprise decisions, purpose, and results, and connects to team strategy, priorities and contributions.
• Risk Manager: Ensures proper risk discipline, controls and culture are in place to identify, escalate and debate issues.
• People Manager & Coach: Provides inspection, coaching and feedback to motivate, differentiate and improve performance.
• Financial Steward: Actively manages expenses and budgets in alignment with objectives, making sound financial decisions.
• Enterprise Talent Leader: Assesses talent and builds bench strength for roles across the organization.
• Driver of Business Outcomes: Delivers results by effectively prioritizing, inspecting and appropriately delegating team work.
Qualifications:
Required:
• Intermediate to advanced knowledge of one or more of the following: SQL, SAS, Alteryx, Python, Tableau or related tools.
• Advanced skills in Microsoft Excel.
• Advanced analytic skills that demonstrate the ability to navigate systems, access data, reconcile numbers from different sources, identify discrepancies and trends, and understand drivers of changes within data.
• Strong track record of implementing automated solutions related to data & analytics, including the ability to extract, organize, and present the data in user-friendly reports, dashboards or tools.
• Ability to work both independently or in teams on multiple projects simultaneously to deliver timely and complete solutions under minimal supervision.
• Strong written and oral communication skills, with ability to communicate with both technical and executive audience.
Preferred:
• Experience with one or more of the following as plus: model development, machine learning/artificial intelligence (AI), and data science.
• Experience with one or more of the following a plus: DataRobot, Instabase, and UIPath.
Company:
The world doesn't have a talent shortage. It has a talent alignment problem. MDA Edge exists to fix that. Founded in , the company is headquartered in Sheridan, WY, US, , with a team of 51-200 employees. The company is currently Growth Stage.