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Full Stack Data Engineer Jobs in New York (NOW HIRING)

Patlytics

Full Stack Engineer

New York, NY · On-site

Full Stack Software Engineer About Patlytics: Patlytics is the fastest-growing AI-native patent ... Work on our core backend service, AI platform, and data pipeline service to provide a scalable and ...

Photon

Full Stack Engineer

Parsippany Troy Hills, NJ · On-site

Full Stack Engineer (React.js / NestJS / TypeScript / Node.js / Google Cloud Platform) Parsippany ... Design and optimize data models using NoSQL databases, particularly Firebase Firestore. * Develop ...

Icon Health

Full Stack Engineer

Stamford, CT · On-site +1

Full Stack Engineer Location: Remote Reports To: SVP, Data and Technology Who We Are Icon Health is a leading provider of value-based musculoskeletal (MSK) care, collaborating with payers and ...

Icon Health

Full Stack Engineer

Stamford, CT · Remote

Full Stack Engineer Location: Remote Reports To: SVP, Data and Technology Who We Are Icon Health is a leading provider of value-based musculoskeletal (MSK) care, collaborating with payers and ...

Cross River

Full Stack Engineer

Fort Lee, NJ

$160K - $200K/yr

Design systems for extreme speed, reliability, and real-time data processing under high traffic ... Actively upskill fellow engineers on full-stack best practices, LLM integration patterns, and ...

Claim Health

Full Stack Engineer

New York, NY · On-site

$150K - $200K/yr

Full Stack Engineer Location: NYC (In-Person) Compensation: Competitive salary + meaningful equity ... Dig into disconnected and messy data to create abstractions that allow for operational scale and ...

Axelon Services Corporation

Java Full Stack

Jersey City, NJ · On-site

$57.50 - $74.25/hr

... data processing layers, optimizing for efficiency and reliability. • Mentor junior and mid-level full-stack developers, providing technical guidance, conducting code reviews, and promoting a ...

New

Cross River

Full Stack Engineer

Fort Lee, NJ · On-site

The Full Stack Engineer will lead the design and architecture of the LLM-based platform ... Own the strategies for scaling to handle high traffic and complex real-time data processing. • ...

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Showing results 1-20

All JobsFull Stack Data Engineer JobsFull Stack Data Engineer Jobs in New York

Full Stack Data Engineer information

See New York salary details

$48.7K

$147.4K

$208.4K

How much do full stack data engineer jobs pay per year?

As of Jun 26, 2026, the average yearly pay for full stack data engineer in New York is $147,444.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,400.00 and $172,900.00 per year, depending on experience, location, and employer.

What is the difference between Full Stack Data Engineer vs Data Scientist?

AspectFull Stack Data EngineerData Scientist
CredentialsBachelor's/Master's in CS, Data Engineering certificationsBachelor's/Master's in CS, Data Science or related fields
Work EnvironmentBuild data pipelines, manage databases, develop APIsAnalyze data, create models, generate insights
Industry UsageTech, finance, healthcare, where data infrastructure is keyResearch, analytics, product development teams

Full Stack Data Engineers focus on building and maintaining data infrastructure, integrating data from various sources, and ensuring data availability. Data Scientists analyze data, develop models, and generate insights. While both roles require strong technical skills, Full Stack Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

What are the key skills and qualifications needed to thrive as a Full Stack Data Engineer, and why are they important?

To thrive as a Full Stack Data Engineer, you need strong expertise in data modeling, ETL processes, and proficiency in both backend (e.g., Python, Java) and frontend (e.g., JavaScript, React) development, often supported by a degree in computer science or a related field. Familiarity with cloud platforms (such as AWS or Azure), big data tools (like Spark or Hadoop), and database systems (SQL and NoSQL) is typically required, and certifications in these technologies are advantageous. Excellent problem-solving, communication, and collaboration skills help you bridge gaps between data, development, and business teams. These skills ensure you can design, build, and maintain scalable data solutions that meet organizational needs efficiently.

How does a Full Stack Data Engineer typically balance responsibilities between backend data infrastructure and frontend data presentation tasks?

Full Stack Data Engineers are often required to split their time between developing robust backend data pipelines and creating user-facing tools or dashboards that visualize data insights. This dual responsibility means you'll need to prioritize tasks based on project needs, effectively collaborating with data scientists, analysts, and frontend developers. Communication is key, as you'll bridge gaps between technical teams and business stakeholders, ensuring data flows seamlessly from source systems to end users. Over time, many engineers find opportunities to specialize further or move into leadership roles overseeing data architecture and team strategy.

What is a Full Stack Data Engineer?

A Full Stack Data Engineer is a professional who designs, builds, and maintains the entire data pipeline, from data collection and storage to processing and visualization. They work with both the backend infrastructure (such as databases, data warehouses, and ETL processes) and frontend tools (like dashboards or reporting systems) to ensure data is accessible and usable for analytics. Full Stack Data Engineers possess skills in programming, database management, data modeling, cloud platforms, and often data visualization, allowing them to manage every stage of data flow within an organization.
What are popular job titles related to Full Stack Data Engineer jobs in New York? For Full Stack Data Engineer jobs in New York, the most frequently searched job titles are:
What job categories do people searching Full Stack Data Engineer jobs in New York look for? The top searched job categories for Full Stack Data Engineer jobs in New York are:
What cities in New York are hiring for Full Stack Data Engineer jobs? Cities in New York with the most Full Stack Data Engineer job openings:
Full Stack Data Engineer jobs near you
Infographic showing various Full Stack Data Engineer job openings in New York as of June 2026, with employment types broken down into 3% As Needed, 90% Full Time, and 7% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $147,444 per year, or $70.9 per hour.
Senior Vice President, Full Stack Data Engineer

Senior Vice President, Full Stack Data Engineer

BNY Mellon

Manhattan, NY • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

BNY Mellon rating

7.7

Company rating: 7.7 out of 10

Based on 46 frontline employees who took The Breakroom Quiz

99th of 139 rated financial services

Job description


Senior Vice President , Full-Stack Data Engineer
At BNY, our culture allows us to run our company better and enables employees' growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world's investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.
Recognized as a top destination for innovators and champions of inclusion, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance - and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary.
We're seeking a future team member for the role of Senior Vice President , Full-Stack Data Engineer to join our Engineering Hub Analytics team. This role is located in New York, NY
This is a hands-on senior individual contributor role embedded within the Engineering Hub Analytics practice. The Data Engineer owns data platform delivery across client engagements - designing, building, and hardening production-grade data pipelines, warehouse architectures, and data infrastructure that power AI and analytics capabilities. This is not a consulting or coordination role; it is an engineering role with full delivery ownership.
In this role, you'll make an impact in the following ways:
  • Design, build, and harden production data pipelines, ELT/ETL workflows, and data platform components across client engagements - moving confidently from prototype to scalable, observable production deployment.
  • Embed with business and platform stakeholders to scope and execute time-boxed data engineering engagements with clear entry and exit criteria; translate defined data opportunities into production-ready delivery plans.
  • Architect and implement data infrastructure across ingestion, transformation, serving, and governance layers using modern tooling (dbt, Airflow/Prefect, Spark, Snowflake, Databricks, cloud-native services).
  • Build and integrate data pipelines that feed AI and analytics systems - including feature stores, RAG knowledge bases, semantic search indexes, and LLM context pipelines.
  • Default to reuse-first delivery: extend existing data platform patterns, templates, and pipeline modules rather than building avoidable one-offs; contribute reusable data assets back to shared repositories.
  • Apply data quality, observability, and operational readiness practices consistently - including lineage tracking, schema validation, SLA monitoring, and alerting.
  • Execute discovery with data owners, analytics teams, and sponsors to clarify data contracts, validate feasibility, and rapidly prototype before hardening into production.
  • Prepare clear handoff packages and transition plans - including data dictionaries, lineage documentation, pipeline runbooks, and ownership transfer artifacts - so receiving teams can sustain solutions independently.
  • Surface reusable data patterns and learnings from engagements that can be standardized and promoted into shared platform capabilities.
  • Coordinate with architecture, security, compliance, and governance stakeholders to ensure data solutions are production-appropriate, lineage-traceable, and governance-compliant.
  • Mentor junior data engineers; contribute to team delivery quality, standards, and knowledge sharing.

To be successful in this role, we're seeking the following:
  • Bachelor's degree in computer science or a related discipline, or equivalent work experience required; advanced degree is beneficial
  • 10-14 years of diverse experience in multiple areas of information technology required; experience in the securities or financial services industry is a plus.
  • Mentors junior data engineers within engagements; contributes to team delivery quality, pipeline standards, and knowledge sharing.
  • Deep experience designing and operating production ELT/ETL pipelines, data warehouse/lakehouse architectures, and cloud data infrastructure.
  • Hands-on experience with modern data tooling: dbt, Airflow or Prefect, Spark, Snowflake or Databricks or BigQuery, and cloud-native data services (AWS, Azure, or GCP).
  • Experience working across the full data stack - ingestion, transformation, serving, governance, and quality - rather than only within a single layer.
  • Experience delivering data infrastructure that feeds AI/ML systems, including feature engineering pipelines, vector stores, RAG knowledge pipelines, or LLM context preparation workflows.
  • Experience operating in regulated environments (financial services, healthcare) with data governance, lineage, and compliance requirements.
  • Strong data modeling judgment: dimensional modeling, data vault, OBT patterns - knowing when to apply which and why.
  • Comfort operating in ambiguity and driving data discovery with senior stakeholders and data owners.
  • Experience with metadata management and governance platforms (Collibra, DataHub, OpenMetadata).
  • Familiarity with real-time and streaming data patterns (Kafka, Kinesis, Flink) as a complement to batch workloads.
  • Experience balancing pipeline velocity with data quality, observability, and SLA commitments.
  • Strong Java\Python engineering skills for pipeline development; SQL fluency (T-SQL, PL/SQL, or equivalent) for transformation and analysis.
  • Experience with dbt for transformation layer development and testing.
  • Proficiency with orchestration tooling: Airflow, Prefect, or equivalent.
  • Cloud data platform experience: Snowflake, Databricks, BigQuery, or Redshift in production.
  • Familiarity with cloud infrastructure relevant to data workloads: AWS (Glue, Lambda, Step Functions, S3, Redshift), Azure (Data Factory, Synapse, ADLS), or GCP (Dataflow, BigQuery, Cloud Composer).
  • Data quality and observability tooling: Great Expectations, Monte Carlo, dbt tests, or equivalent.
  • Version control, CI/CD, and DevOps practices applied to data pipeline development (DataOps).
  • Strong written and verbal communication across technical and non-technical audiences, including data owners, analytics consumers, and platform stakeholders.
  • Clear data product and delivery judgment within a scoped engagement.
  • Ability to coordinate and execute across stakeholders - data owners, platform engineers, analytics teams - without formal authority.
  • Practical tradeoff thinking: pipeline complexity vs. maintainability, freshness vs. cost, schema flexibility vs. governance.
  • Bias toward action with disciplined follow-through on data quality and operational readiness.

At BNY, our culture speaks for itself, check out the latest BNY news at:
BNY Newsroom
BNY LinkedIn
Here's a few of our recent awards:
  • America's Most Innovative Companies, Fortune, 2025
  • World's Most Admired Companies, Fortune 2025
  • "Most Just Companies", Just Capital and CNBC, 2025

Our Benefits and Rewards:
BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life's journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter.
BNY Mellon is an Equal Employment Opportunity/Affirmative Action Employer.Minorities/Females/Individuals with Disabilities/Protected Veterans.Our ambition is to build the best global team - one that is representative and inclusive of the diverse talent, clients and communities we work with and serve - and to empower our team to do their best work. We support wellbeing and a balanced life, and offer a range of family-friendly, inclusive employment policies and employee forums.
BNY assesses market data to ensure a competitive compensation package for our employees. The base salary for this position is expected to be between $116,500 and $220,000per year at the commencement of employment. However, base salary if hired will be determined on an individualized basis, including as to experience and market location, and is only part of the BNY total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, short and long-term incentive packages, and Company-sponsored benefit programs.
This position is at-will and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation) at any time, including for reasons related to individual performance, change in geographic location, Company or individual department/team performance, and market factors.

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About BNY Mellon

Sourced by ZipRecruiter

BNY Mellon is a global investments company dedicated to helping its clients manage and service their financial assets throughout the investment lifecycle. Whether providing financial services for institutions, corporations or individual investors, BNY Mellon delivers informed investment and wealth management and investment services in 35 countries. As of Dec. 31, 2021, BNY Mellon had $46.7 trillion in assets under custody and/or administration, and $2.4 trillion in assets under management. BNY Mellon can act as a single point of contact for clients looking to create, trade, hold, manage, service, distribute or restructure investments. BNY Mellon is the corporate brand of The Bank of New York Mellon Corporation (NYSE: BK). Additional information is available on www.bnymellon.com . Follow us on Twitter @BNYMellon or visit our newsroom at www.bnymellon.com/newsroom for the latest company news.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1784

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