689 Data Analytics Engineer jobs in New York,NY

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Sr. Data Engineer

Subway Restaurants

Bridgeport, CT 06606

$119,200-$149,000/yr

~ 1 hr 13 min OnsiteEducation AssistanceHealth InsuranceRetirement Benefit

Bachelor's degree in Computer or Information Science or related field, or equivalent combination of education and experience
5–8 years creating quality data pipelines and system integrations
At least 3 years of experience in a cloud environment
Hands-on experience building lakehouse solutions on Databricks (Delta Lake, Unity Catalog) or Snowflake (Iceberg Tables, Horizon Catalog)
Proven ability to design Bronze/Silver/Gold layers for curated, analytics-ready data
Experience implementing Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake Dynamic Tables / Snowpipe Streaming
Experience building and managing semantic models using Databricks AI/BI Genie or Unity Catalog Metrics or Snowflake Semantic Views / Cortex Analyst
Building pipelines with Airflow, Databricks Lakeflow, or Snowflake Openflow; familiarity with dbt is a plus
Strong PySpark or advanced SQL skills; Python for data engineering or automation
Dimensional modeling, Data Vault, or schema design for analytical workloads
Cluster/warehouse sizing, partitioning, clustering keys, Z-ordering, or query optimization
Working knowledge of Unity Catalog (Databricks) or Horizon Catalog (Snowflake) for lineage, access control, or data quality
Git, Databricks Asset Bundles or Snowflake CLI/Schemachange, automated testing, or deployment pipelines
AWS (S3, Glue, Kinesis), Azure, or GCP services supporting modern data platforms
Familiarity with Databricks Mosaic AI or Snowflake Cortex for GenAI or ML use cases
Strong communication skills to partner with Product Owners, Analysts, or cross-functional engineering teams
Authorized to work in the country the position is based

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Senior AWS Redshift Data Engineer (Contract | 1099)

BrainTrust

New York, NY 10001

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Human Resources Technology Data Engineer

LHH US

Astoria, NY 11106

$85-$100/hr

Hybrid~ 12 minHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in Computer Science, Engineering, or a related field.
5-8 years of professional software engineering experience.
Proven track record of hands on development in enterprise scale systems, preferably in HR.
Strong proficiency in at least one core programming language (Python or Java).
Deep experience with relational databases, NoSQL stores, and complex query design.
Experience working with HR, people operations, or workforce analytics data, including sensitive data handling, HRIS integrations (e.g., Dayforce, Culture Amp, etc.), and secure data exchange patterns.
Demonstrated ability to build or support platforms involving employee lifecycle data, compensation structures, organizational hierarchies, and talent management workflows.

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Software Engineering/Applications Leadership Advisory - Executive Technology Services for Global Enterprises

Gartner

Newark, NJ 07175

New, Posted 1 day ago

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Sr Business Analytics Advisor (US Remote)

FedEx Logistics

Jamaica, NY 11434

RemoteEducation AssistanceHealth InsuranceRetirement Benefit

Bachelor's degree/equivalent in engineering, data analytics, computer software or related technical or quantitative discipline.
Five (5) years experience in data analytics, data management and/or engineering
Excellent analytical, problem solving, presentation, project management, SQL, data analytics tools (e.g. SAS), data visualization tools (e.g., Tableau, SAS VA, Spotfire)
Excellent human relations, organizational/time management and communication skills.

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Manufacturing Engineer

Whippany Actuation Systems

Whippany, NJ 07981

$90,000-$110,000/yr

~ 50 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

A bachelor's degree in manufacturing, Aerospace, or Mechanical Engineering from an accredited university or college;
One year of experience in a manufacturing environment which includes interpreting blueprints and familiarity with GD&T;
Previous experience with CAD systems;

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New Product Manufacturing Engineer

CACI International Inc

Florham Park, NJ 07932

~ 50 min Onsite

Ability to work independently with minimal supervision and mentor lower-level professionals.
Must be a US person.
BA/BS degree in a technical discipline from an accredited college or university.
Minimum of five (5) years of experience as a manufacturing engineer or in a related role.
Percentage of Travel Required: Up to 10%
Type of Travel: Local

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Director of Engineering

Marine Electric Systems

South Hackensack, NJ 07606

~ 26 min OnsiteHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in Electrical Engineering or a closely related engineering discipline.
Significant experience in electrical engineering, sustaining engineering, production engineering, test engineering, or engineering leadership in a manufacturing environment.
Strong hands-on technical knowledge of electrical and electromechanical systems.
Experience with PCB troubleshooting, electrical testing, components, assemblies, and production support.
Ability to read and interpret drawings, schematics, specifications, technical data packages, and test procedures.
Experience supporting manufacturing, production, repair, or sustainment work.
Ability to make practical engineering decisions with imperfect information.
Strong communication skills and ability to work cross-functionally with production, quality, procurement, sales, and leadership.
Demonstrated ability to mentor junior engineers or technical staff.
Strong organizational skills and ability to create structure in a fast-moving small-company environment.

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Principal Engineer - Python API Development

Fidelity Investments

Hoboken, NJ 07030

~ 16 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's or Master's degree in Computer Science, Software Engineering, or a closely related engineering discipline
8+ years (typically 10+) building and operating production platforms and services at scale
Deep software engineering expertise in Python and distributed systems
A track record of building production‑grade services, libraries, and internal platforms
Linux fluency and scripting are required
Cloud platform leadership (AWS) —hands-on with S3, Lambda, Batch, Step Functions, EventBridge, CloudWatch, and SNS/SQS—and experience shaping platform patterns that other teams adopt
Experience enabling managed ML services (e.g., SageMaker) as part of broader platform capabilities; exposure to Azure or GCP is beneficial
DevOps and CI/CD at scale, owning standards for automated build/test/deploy (e.g., Jenkins, Git‑based workflows), containerization (Docker), release governance, and multi‑environment promotion for ML‑enabled workloads
Infrastructure as Code (CloudFormation, Terraform/OpenTofu) and platform reliability engineering (SLOs/error budgets, capacity planning, cost observability, incident response, and post‑mortems) for ML serving and data/feature pipelines
ML enablement in production: model packaging, deployment strategies (batch/online/streaming), inference routing, traffic management, performance tuning, observability, and controls for responsible use—without a research or modeling focus
Cross‑org technical leadership: you mentor junior and senior engineers, are a backbone of code review across repos, and routinely consider impacts on upstream/downstream systems when proposing changes
Set platform strategy and standards for ML packaging, deployment, serving, and observability—driving consistent adoption across squads and business units
Partner with Data Scientists to package, scale, and operationalize models; define the APIs, guardrails, and automation that take work from experimentation to reliable production
Enable secure, scalable access to traditional and generative models by collaborating with platform and application engineers to integrate through enterprise gateways and services
Advance model/data observability—tooling for data and feature drift detection, prediction‑quality monitoring and uncertainty signals, and automated diagnostics/ explainability
Lead cross‑platform incident response and post‑mortems, drive systemic fixes, and evolve standards to prevent recurrence—across applications and the platform
Uplevel engineering velocity by introducing reusable frameworks, paved paths, and CI/CD templates that simplify integration, reduce toil, and improve reliability at scale
Reduce cost and complexity across the ML ecosystem through pragmatic technology choices, clear abstractions, and a long‑term platform roadmap
The base salary range for this position is $107,000-216,000 USD per year.
Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.