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Associate Data Engineer Jobs in Morganville, NJ (NOW HIRING)

Data Engineer

New York, NY · On-site +1

$125K - $150K/yr

This position is ideal for an engineer who is passionate about data, eager to learn emerging ... Humana reserves the right to require associates to upgrade their internet service if necessary.

New

Data Engineer

New York, NY · On-site

$125K - $150K/yr

Azure or Databricks certifications (e.g., Azure Data Engineer Associate, Azure Solutions Architect Expert, Databricks Data Engineer Professional) are a plus. We are GEI. Some of the world's most ...

Databricks Certified Data Engineer Associate or Professional certification is considered an advantage but is not required. W2 employees of Overture Partners who work 30 or more hours per week are ...

Specialist Data Engineer

New York, NY · Hybrid

$114K - $134K/yr

Azure Data Engineer Associate is preferred. * Microsoft Certified: Azure Data Fundamentals is preferred. Knowledge, Skills and Abilities: * Strong knowledge of Big Data architectures, large data ...

... Associate, Snowflake Core, Snowflake Architect, Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies - Developing and documenting data ...

Principal Data Engineer

New York, NY · On-site

$125K - $226K/yr

Job Overview We're looking for a Principal Data Engineer who brings strong technical judgment, a ... Associate (MCSA) (Required) * At least 18 years of age * Legally authorized to work in the United ...

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Associate Data Engineer information

See Morganville, NJ salary details

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How much do associate data engineer jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for associate data engineer in Morganville, NJ is $18.52, according to ZipRecruiter salary data. Most workers in this role earn between $15.19 and $19.71 per hour, depending on experience, location, and employer.

What does an associate data engineer do?

An Associate Data Engineer is responsible for supporting the development, maintenance, and optimization of data pipelines and databases. They work closely with senior data engineers and other IT professionals to ensure data is accessible, reliable, and efficiently processed for analytics and business use. Typical tasks include writing and testing code for data integration, troubleshooting data issues, and implementing data security best practices. This entry-level position is a foundational role that builds technical skills and experience in data engineering.

What are the key skills and qualifications needed to thrive as an associate data engineer?

To thrive as an Associate Data Engineer, you need a solid understanding of data modeling, SQL, Python, and foundational knowledge of database concepts, often backed by a degree in computer science or a related field. Familiarity with data warehousing tools (like AWS Redshift, Google BigQuery), ETL frameworks, and cloud platforms as well as industry certifications such as AWS Certified Data Analytics is beneficial. Strong problem-solving skills, attention to detail, and effective communication help you navigate complex data challenges and collaborate with teams. These abilities are crucial for ensuring data systems are reliable, scalable, and aligned with organizational goals.

What are some common challenges an associate data engineer may face when working with large-scale data pipelines?

As an Associate Data Engineer, you may often encounter challenges such as optimizing data pipeline performance, ensuring data quality, and troubleshooting bottlenecks when processing large volumes of data. Working with distributed systems can introduce complex issues like latency and data consistency. Collaborating effectively with data scientists, analysts, and senior engineers is crucial for aligning data infrastructure with evolving project requirements. Regularly learning new tools and best practices will help you adapt to these challenges and grow in your role.

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

AspectAssociate Data EngineerData Engineer
Required CredentialsBachelor's degree in CS, Data Science, or related field; basic knowledge of SQL and PythonBachelor's or Master's degree; advanced knowledge of SQL, Python, Spark, and cloud platforms
Work EnvironmentEntry-level, team-focused, often in tech or finance industriesMid to senior level, designing and maintaining data pipelines in various industries
Employer & Industry UsageCommon in tech companies, startups, and finance firmsUsed across industries for building scalable data infrastructure
Common Search & ComparisonOften compared for career progression and skill requirements

The Associate Data Engineer role is an entry-level position focusing on supporting data infrastructure, while the Data Engineer is a more advanced role responsible for designing and maintaining complex data systems. The roles share similar educational backgrounds and work environments but differ in experience level and responsibilities.

Is an associate data engineer entry level?

An associate data engineer is typically an entry-level position suitable for candidates with limited professional experience in data engineering. It often requires foundational skills in SQL, Python, or cloud platforms and serves as a starting point for a career in data engineering.

What are the most commonly searched types of Data Engineer jobs in Morganville, NJ?

The most popular types of Data Engineer jobs in Morganville, NJ are:

What are popular job titles related to Associate Data Engineer jobs in Morganville, NJ?

For Associate Data Engineer jobs in Morganville, NJ, the most frequently searched job titles are:

What job categories do people searching Associate Data Engineer jobs in Morganville, NJ look for?

The top searched job categories for Associate Data Engineer jobs in Morganville, NJ are:

What cities near Morganville, NJ are hiring for Associate Data Engineer jobs?

Cities near Morganville, NJ with the most Associate Data Engineer job openings:

Associate Data Engineer, Data Management - Data Office

New York, NY

Full-time

Medical, Retirement

Posted 2 days ago

New


BlackRock rating

7.8

Company rating: 7.8 out of 10

Based on 14 frontline employees who took The Breakroom Quiz


Job description

hackajob is collaborating with BlackRock to connect them with exceptional professionals for this role.

About this role

What team will you be on?

The BlackRock Data Office (BDO) builds and advances the firm's enterprise data capabilities through trusted, scalable, and governed data products that power investment, business, operational, and technology outcomes across BlackRock.

As part of the Data Office organization, you will work closely with product managers, data stewards, platform engineers, software engineers, data scientists, and business stakeholders to deliver reusable data capabilities that support analytics, reporting, machine learning, artificial intelligence, and digital products.

Why is your role important?

As a Data Engineer, you will play a key role in designing, building, and optimizing modern data platforms and pipelines that enable high-quality, reliable, and accessible data across the organization.

Depending on experience and level, you will contribute to or lead the design and implementation of complex data engineering solutions, influence technical direction, and help establish engineering best practices across the organization.

This role offers the opportunity to solve complex data challenges, build scalable distributed systems, and shape the next generation of enterprise data products and capabilities.

What will you be doing?

In every role at BlackRock, you'll be expected to apply sound judgement and critical thinking to solve complex problems, adapt as the business evolves, and combine the curiosity to explore new approaches and technologies with the rigor to challenge the results. The scope of this role also includes the following responsibilities.

  • Design, develop, and maintain scalable, reliable, and high-performance data pipelines supporting enterprise data products.

  • Build and optimize batch and real-time data ingestion, transformation, and publishing processes across diverse data sources.

  • Develop reusable data engineering frameworks, components, and automation to improve platform efficiency and developer productivity.

  • Ensure data products meet enterprise standards for quality, security, governance, lineage, and observability.

  • Keep data separated and segregated according to relevant data policies.

  • Identify opportunities to improve performance, scalability, resiliency, and cost optimization across the data platform.

  • Troubleshoot complex production issues, perform root cause analysis, and implement sustainable long-term solutions.

  • Contribute to engineering standards, code reviews, testing practices, continuous integration and continuous delivery (CI/CD) automation, and technical documentation.

  • Automate manual ingestion processes and optimize data delivery subject to service-level agreements while partnering with infrastructure teams to improve scalability.

  • Stay current on emerging technologies and recommend innovative approaches that improve the firm’s data ecosystem.

  • Associate: Deliver high-quality engineering solutions while continuing to deepen technical expertise across modern data technologies.

What are we looking for?

  • Demonstrated ability to collaborate across global, cross-functional teams including data stewards, data scientists, platform engineers, and business stakeholders, and take ownership of major components of the data platform ecosystem.

  • Strong programming skills in Python, Java, and Scala, with experience working across large-scale distributed data analytics engines, cloud data platforms, Snowflake, and Structured Query Language (SQL).

  • Experience integrating and transforming data from flat-file sources such as comma-separated values (CSV), tab-separated values (TSV), Microsoft Excel, and database application programming interface (API) sources.

  • Associate: Typically 3–6 years of relevant experience in software engineering, data engineering, or related technical disciplines.

  • 4+ years of strong Java, Python, or Scala programming experience, including hands-on experience developing user-defined functions (UDFs), reusable modules, and automated testing with frameworks such as pytest.

  • 4+ years of experience building and optimizing large-scale data pipelines, architectures, and datasets. Familiarity with directed acyclic graph-based workflow orchestration frameworks for data and batch processing, dbt, and distributed event streaming and messaging platforms.

  • 4+ years of hands-on experience developing production workloads using large-scale distributed data analytics engines, including resource allocation, performance tuning, and job optimization.

  • 4+ years of experience using SQL-based analytics layers over large-scale data platforms, workload-monitoring tools, and data-optimization techniques including bucketing, partitioning, tuning, and schema-based data serialization and interchange formats.

  • 4+ years of experience using Transact-SQL, relational databases, non-relational databases, and GraphQL.

  • Strong experience implementing solutions on Snowflake.

  • Experience with data-quality and validation frameworks, particularly Great Expectations.

  • Strong understanding of Swagger/OpenAPI for designing, documenting, and testing RESTful APIs.

  • Experience deploying and supporting solutions across cloud and hybrid environments, including Amazon Web Services (AWS), Microsoft Azure, OpenStack, Open Container Initiative (OCI) container image packaging and runtime, distributed event streaming and messaging platforms, and enterprise-grade container orchestration platforms supporting declarative infrastructure and horizontal scaling.

  • Familiarity with CI/CD pipelines for data-platform automation and deployment using tools such as Jenkins, GitLab CI, and Azure DevOps.

  • Experience with data governance, metadata management, and data lineage, including business glossaries, access controls, auditing, and centralized governance across cloud and hybrid environments.

  • Hands-on experience with Databricks, including notebooks, workflows, and machine learning integrations.

  • Experience working across global, cross-functional teams in a collaborative and fast-paced engineering environment.

  • Exposure to machine learning, artificial intelligence, generative AI, or engineering patterns that support AI-ready data platforms is beneficial.

Our benefits
To help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.

Our hybrid work model

BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.


Guidance on AI use for candidates

At BlackRock, AI has long been part of how we work – enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we’ve provided guidance on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self.

About BlackRock

At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being.  Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.

This mission would not be possible without our smartest investment – the one we make in our employees. It’s why we’re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.

To learn more about BlackRock, please visit Careers.BlackRock.com. We also encourage you to get to know us on LinkedIn, Instagram, YouTube, X, and TikTok.

BlackRock is proud to be an equal opportunity workplace. We are committed to equal employment opportunity to all applicants and existing employees, and we evaluate qualified applicants without regard to race, creed, color, national origin, sex (including pregnancy and gender identity/expression), sexual orientation, age, ancestry, physical or mental disability, marital status, political affiliation, religion, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law. View the EEOC’s Know Your Rights poster and its supplement and the pay transparency statement.

BlackRock is committed to full inclusion of all qualified individuals and to providing reasonable accommodations or job modifications for individuals with disabilities. If reasonable accommodation/adjustments are needed throughout the employment process, please email Disability.Assistance@blackrock.com. All requests are treated in line with our privacy policy.

BlackRock will consider for employment qualified applicants with arrest or conviction records in a manner consistent with the requirements of the law, including any applicable fair chance law.


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