data engineer

data analyst

software engineer

data scientist

software engineer, full stack Jobs in New York

software engineer, full stack

data pipeline engineer

New York Life

<div><div><div>Job Description</div></div><div><div><div><h4 class="jobSectionHeader">
Requisition ID</h4><div>
93907</div></div><div><h4 class="jobSectionHeader">
Department</h4><div>
Tech Data AI Ventures</div></div><div><h4 class="jobSectionHeader">
Job Function</h4><div>
Tech Data AI Ventures</div></div><div><h4 class="jobSectionHeader">
Location</h4><div>
New York,New York,United States</div></div><div><h4 class="jobSectionHeader">
Role Location Designation</h4><div>
Fully Onsite</div></div></div></div><div><div><div><div><div>
Job Requisition ID: 93907</div>
Location Designation: Fully Onsite<div>
Location: 51 Madison Avenue, New York, New York 10010</div><div></div><div> 
Salary Range: $144,400.00 - $171,500.00/year</div><div></div> 
Duties: Design and implement data pipeline architecture and processes including sourcing, transformation, and extraction to enable seamless analytics integration. Utilize expert-level SQL and Python to manage, query, and transform structured data in relational databases to ensure performance, scalability, and maintainability. Automate and manage robust data pipelines and workflows using software engineering best practices including modular design, version control, and testing frameworks to ensure reliability and repeatability. Map data between source systems, data warehouses, and data marts in alignment with business requirements, ensuring data consistency across analytical workflows. Build and maintain data models that enhance efficiency, performance, and support complex business analytics and reporting needs. Collaborate with analysts, data scientists, and business stakeholders to translate business requirements into actionable, scalable data solutions. Leverage cloud platforms including AWS, along with big data frameworks like Redshift, to build and scale secure, high-performance data engineering solutions for large-scale analytics. Develop and enforce standards for development, testing and documentation, including data flow maps to support transparency and maintainability. Conduct comprehensive quality assurance processes including code reviews, test plan development, and rigorous validation to ensure data accuracy, completeness, and reliability. Provide troubleshooting support for data pipelines and workflows, focusing on system performance, data integrity, and availability to meet evolving business analytics demands. Build strong relationships with IT to work on tooling, data strategy, integrations, and deployments. Stay up to date with the latest analytics engineering trends and emerging technologies, and look for opportunities to improve the stack. 
Education &amp; Experience Requirements: Master's degree in Computer Science, Computer Engineering, Business Analytics or related field (willing to accept foreign education equivalent) plus three (3) years of experience as a Data Analyst or Data Engineer supporting data science and analytics through data engineering, pipeline development, and cross-functional collaboration across data, IT, and business teams. Alternatively, Bachelor's degree in Computer Science, Computer Engineering, Business Analytics or related field (willing to accept foreign education equivalent) plus five (5) years of experience as a Data Analyst or Data Engineer supporting data science and analytics through data engineering, pipeline development, and cross-functional collaboration across data, IT, and business teams. Specific skills/other requirements - Experience must include (quantitative experience requirements not applicable to this section): Utilizing advanced-level SQL and Python for querying and managing structured data within relational database systems (RDBMS). Designing and implementing data models to enhance efficiency, performance, and fulfill business analytics requirements. Automating and orchestrating SQL workflows using established software engineering best practices including CI/CD and version control. Developing standards and practices for data and analytics engineering, focusing on scalable architectural data pipeline patterns. Utilizing big data platforms including Redshift for efficient large-scale data processing and analysis. Building and deploying scalable data engineering solutions in cloud environments including AWS using cloud-native tools and services. Conducting comprehensive quality assurance processes including code reviews, test plan development, and rigorous validation to ensure data accuracy. Hybrid &ndash; 3 days in office, 2 days remote. Eligible for Employee Referral Program. To apply, visit https://jobs.newyorklife.com/ and search job title. 
Pay Transparency
Overtime eligible: Exempt
Discretionary bonus eligible: No
Sales bonus eligible: No
Actual base salary will be determined based on several factors but not limited to individual&rsquo;s experience, skills, qualifications, and job location. Additionally, employees are eligible for an annual discretionary bonus. In addition to base salary, employees may also be eligible to participate in an incentive program.<div> 
Company Overview</div><div>
At New York Life, our 180-year legacy of purpose and integrity fuels our future. As we evolve into a more technology-, data-, and AI-enabled organization, we remain grounded in the values that drive lasting impact.</div><div>
Our diverse business portfolio creates opportunities to make a difference across industries and communities&mdash;inviting bold thinking, collaborative problem-solving, and purpose-driven innovation. Here, you&rsquo;ll find the rare balance of long-standing stability and forward momentum, supported by an inclusive team that honors tradition while embracing progress.</div><div>
As a Fortune 100 mutual company, we offer a place to grow your skills, contribute to meaningful work, and deliver solutions that matter. Your ideas drive what&rsquo;s next, and your growth powers it.</div> 
Our Benefits
We provide a full package of benefits for employees &ndash; and have unique offerings for a modern workforce, including leave programs, adoption assistance, and student loan repayment programs. Based on feedback from our employees, we continue to refine and add benefits to our offering, so that you can flourish both inside and outside of work. Click here to discover more about our comprehensive benefit options or visit our NYL Benefits Site. 
Our Commitment to Inclusion 
At New York Life, fostering an inclusive workplace is fundamental to who we are and how we serve our communities. We have a longstanding commitment to creating an environment where individuals can contribute their best and succeed together. This foundation is rooted in our core values of humanity and integrity, ensuring that every employee feels valued and supported. By embracing a broad range of perspectives and experiences, we achieve greater success and fulfill our promise of providing financial security and peace of mind to families across all communities. Click here to learn more about New York Life&rsquo;s leadership in this space.
Recognized as one of Fortune&rsquo;s World&rsquo;s Most Admired Companies, New York Life is committed to improving local communities through a culture of employee giving and volunteerism, supported by the Foundation. We're proud that due to our mutuality, we operate in the best interests of our policy owners. To learn more about career opportunities at New York Life, please visit the Careers page of www.NewYorkLife.com.
Visit our LinkedIn to see how our employees and agents are leading the industry and impacting communities.
Visit our Newsroom to learn more about how our company is constantly evolving to meet our clients' and employees&rsquo; needs. 
Job Requisition ID: 93907</div></div></div></div></div>

Senior Associate, Analytics Data Engineer

MERCOR

<div><h2 class="jobSectionHeader">About Mercor</h2>
Mercor's mission is to organize human intelligence to power the AI economy. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development. Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You&rsquo;ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.
About the Role
We&rsquo;re looking for someone who wants to bring a full-stack perspective to data. As a Software Engineer supporting our Data function, you will be responsible for creating and maintaining pipelines that enable our Data Science, Engineering, and Product teams, and the wider Mercor organization.
Your focus will be on data reliability, availability, and timeliness, with a focus on collaboration (and significant operational crossover with) our Data Science team and the many partner functions.
What You&rsquo;ll Work On<ul><li>
Building robust pipelines to ingest, transform, and consolidate data from diverse sources (e.g., MongoDB, Airtable, PostHog, production databases).</li><li>
Designing dbt models and transformations to standardize and unify many disparate tables into clean, production-ready schemas.</li><li>
Implementing scalable, fault-tolerant data workflows with Fivetran, dbt, SQL, and Python.</li><li>
Partnering with engineers, data scientists, and business stakeholders to ensure data availability, accuracy, and usability.</li><li>
Owning data quality and reliability across the stack, from ingestion through to consumption.</li><li>
Continuously improving pipeline performance, monitoring, and scalability.</li></ul> 
What We&rsquo;re Looking For<ul><li>
Proven experience in data engineering, with strong knowledge of SQL, Python, and modern data stack tools (Fivetran, dbt, Snowflake or similar).</li><li>
Experience building and maintaining large-scale ETL/ELT pipelines across heterogeneous sources (databases, analytics platforms, SaaS tools).</li><li>
Strong understanding of data modeling, schema design, and transformation best practices.</li><li>
Familiarity with data governance, monitoring, and quality assurance.</li><li>
Comfort working cross-functionally with engineering, product, and operations teams.</li><li>
Bonus: prior experience supporting machine learning workflows or analytics platforms.</li></ul>
Why Mercor<ul><li>
Impact: Your work powers how the world&rsquo;s leading AI labs train and test their models.</li><li>
Learning: Get early insights into frontier model capabilities months before the market.</li><li>
Growth: Work on both infrastructure and research-adjacent projects with fast paths to ownership.</li></ul>
Benefits<ul><li>
Generous equity grant vested over 4 years</li><li>
A $10K housing bonus (if you live within 0.5 miles of our office)</li><li>
A $1K monthly stipend for meals</li><li>
Free Equinox membership</li><li>
Health insurance</li></ul>
Compensation Range: $130K - $500K</div>

Data Engineer

Nscale

<div>
 
 About Nscale
 
 
 
 Nscale is the GPU cloud engineered for AI. We provide cost-effective, high-performance infrastructure for AI start-ups and large enterprise customers. Nscale enables AI-focused companies to achieve superior results by reducing the complexity of AI development. Our GPU cloud bolsters technical capabilities and directly supports strategic business outcomes, including cost management, rapid innovation, and environmental responsibility.
 
 
 We thrive on a culture of relentless innovation, ownership, and accountability, where every team member takes pride in their work and drives it with excellence and urgency. As an Nscaler, you&rsquo;ll build trust through openness and transparency, where everyone is inspired to do their best work. If you join our team, you&rsquo;ll be contributing to building the technology that powers the future.
 
 
 
 About The Role (Job Purpose)
 
 
 
 We&rsquo;re looking for a
 
 Data Engineer
 
 to help design, build, and operate the data foundations that underpin Nscale&rsquo;s platform, internal operations, and customer-facing capabilities.
 
 
 This is a
 
 high-impact, early-stage role
 
 . You&rsquo;ll work closely with Operations, Infrastructure, Platform Engineering, Product, and Commercial teams to turn raw operational signals &mdash; from GPUs, clusters, customers, and internal systems &mdash; into reliable, scalable data products that ensure delivery at a previously unseen pace. You&rsquo;ll help define
 
 how data is collected, modelled, served, and trusted
 
 across the company, and have the opportunity to build on Palantir Foundry, as well as other products.
 
 
 This role is ideal for someone who enjoys building data systems from first principles, thrives in ambiguous environments, and wants to see their work directly influence product decisions, platform reliability, and customer outcomes.
 
 
 
 What You&rsquo;ll Be Doing (Responsibilities)
 
 
 
 
 Data Platform &amp; Architecture
 
 
 
 <ul>
 <li>
 Design and build scalable, reliable data pipelines that ingest data from infrastructure, platform services, and business systems.
 </li>
 <li>
 Define data models and schemas that support operational workflows and use cases across the business, monitoring, and analytics.
 </li>
 <li>
 Clean, transform and structure the data to create a digital twin of Nscale.
 </li>
 <li>
 Implement permissioning and manage access and security of the Foundry implementation.
 
 
 </li>
 </ul>
 
 Data Products &amp; Enablement
 
 
 
 <ul>
 <li>
 Create trusted datasets and metrics that power workflows and processes, internal tools, and customer-facing insights.
 </li>
 <li>
 Enable self-serve analytics by establishing clear data contracts, documentation, and semantic layers.
 </li>
 <li>
 Build use cases including but not limited to capacity planning, cost optimisation, reliability analysis, and customer reporting to drive our business forward.
 </li>
 <li>
 Collaborate with Product and Commercial teams to translate real-world questions into robust data solutions.
 
 
 </li>
 </ul>
 
 Reliability, Quality &amp; Governance
 
 
 
 <ul>
 <li>
 Implement data quality checks, monitoring, and alerting to ensure data correctness and availability.
 </li>
 <li>
 Codify data lineage, freshness, and consistency across systems.
 </li>
 <li>
 Establish best practices around data versioning, access control, and governance appropriate for a fast-scaling company.
 </li>
 <li>
 Continuously improve system resilience and observability.
 
 
 </li>
 </ul>
 
 Early-Stage Ownership &amp; Growth
 
 
 
 <ul>
 <li>
 Take end-to-end ownership of projects, from design through to production and iteration.
 </li>
 <li>
 Help define standards, tooling, and ways of working for data at Nscale.
 </li>
 <li>
 Contribute to technical decision-making as the company scales its platform and customer base.
 </li>
 <li>
 Act as a thought partner to engineers and operators, not just a service function.
 
 
 </li>
 </ul>
 
 About You (Skills / Qualifications)
 
 
 
 <ul>
 <li>
 Deep, hands-on experience building in Palantir Foundry, including ontology modelling, pipeline development, API integration, and large-scale data platform design.
 </li>
 <li>
 Strong proficiency in Python, with experience applying data engineering libraries and frameworks (e.g. Spark, PySpark, Dask, pandas) to work with large, complex datasets.
 </li>
 <li>
 Familiarity with API-driven data integration, including REST, GraphQL, and Foundry Action APIs.
 </li>
 <li>
 Practical experience working in Git-based development workflows, including code reviews, version control, and CI/CD pipelines.
 </li>
 <li>
 Comfort working in ambiguous, early-stage environments where requirements evolve quickly.
 </li>
 <li>
 Strong communication skills &mdash; able to explain data concepts clearly to technical and non-technical stakeholders.
 </li>
 <li>
 A bias toward ownership, pragmatism, and shipping useful solutions.
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Experience with cloud platforms (AWS, GCP, Azure) and infrastructure telemetry.
 </li>
 <li>
 Familiarity with distributed systems, monitoring data, or usage-based billing data.
 </li>
 <li>
 Experience supporting customer-facing data products or platforms.
 
 
 </li>
 </ul>
 
 What We Can Offer You
 
 
 
 At Nscale, you'll find a
 
 collaborative, supportive, and innovative environment
 
 where your contributions spark real impact. We're building something extraordinary, and we want you at the core.
 
 
 <ul>
 <li>
 Highly competitive package (base + equity) with reviews every 12 months. 🚀
 </li>
 <li>
 Join the fastest-growing tech startup, your chance to push boundaries, collaborate with brilliant minds, and make your mark on cutting-edge AI. ✨
 </li>
 <li>
 Expect a dynamic progression plan tailored to your ambitions. Grow by trying new things, leading, challenging the status quo, and owning your impact, always with our full support.
 </li>
 <li>
 Human-First Flexibility: We treat you as humans first. 🫶🏽 Our flexible workplace trusts Nscalers to deliver, giving you the autonomy to shape your day around life's moments.
 </li>
 <li>
 Join our thriving remote-first team. Geography is no barrier to impact or connection. We build seamless virtual collaboration, empowering you, wherever you work.
 
 
 </li>
 </ul>
 
 Interview Process
 
 
 
 <ul>
 <li>
 Phone screen
 </li>
 <li>
 Coding interviews
 </li>
 <li>
 Hiring Manager interview
 
 
 </li>
 </ul>
 
 Equal Opportunities Statement
 
 
 
 We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio-economic backgrounds.
 
 
 If there&rsquo;s anything we can do to accommodate your specific situation, please let us know.
 
 
 The responsibilities outlined in this job description are not exhaustive and are intended to provide a general overview of the position. The employee may be required to perform additional duties, tasks, and responsibilities as assigned by management, consistent with the skills and qualifications required for the role.
 
 
 
 For information on how Nscale handles candidate personal data, please see our Employee &amp; Candidate Privacy Notice: Here.
 
</div>

BlackRock

<div>
 
 About This Role
 
 
 
 <ul>
 <li>
 Improve BlackRock&rsquo;s ability to enhance our retail sales distribution capabilities and services suite by creating, expanding and optimizing our data and data pipeline architecture.
 </li>
 <li>
 You will create and operationalize data pipelines to enable squads to deliver high quality data-driven product.
 </li>
 <li>
 You will be accountable for managing high-quality datasets exposed for internal and external consumption by downstream users and applications.
 </li>
 <li>
 Top technical / programming skills &ndash; Python, Java and Scala with ability to work across big data frameworks such as Spark, Hadoop Suite, PySpark, Hive, Cloud Data Platforms Preferably Snowflake and SQL.  Experience working with flat files (e.g., csv, tsv, Excel), Database API sources is a must to both ingest and create transformations.
 </li>
 <li>
 Given the highly execution-focused nature of the work, the ideal candidate will roll up their sleeves to ensure that their projects meet deadlines and will always look for ways to optimize processes in future cycles.
 </li>
 <li>
 The successful candidate will be highly motivated to create, optimize, or redesign data pipelines to support our next generation of products and data initiatives.
 </li>
 <li>
 You will be a builder and an owner of your work product.
 
 
 </li>
 </ul>
 Responsibilities:
 
 
 <ul>
 <li>
 Lead in the creation and maintenance of optimized data pipeline architectures on large and complex data sets.
 </li>
 <li>
 Assemble large, complex data sets that meet business requirements.
 </li>
 <li>
 Act as lead to identify, design, and implement internal process improvements and relay to relevant technology organization.
 </li>
 <li>
 Work with stakeholders to assist in data-related technical issues and support their data infrastructure needs.
 </li>
 <li>
 Automate manual ingest processes and optimize data delivery subject to service level agreements; work with infrastructure on re-design for greater scalability.
 </li>
 <li>
 Keep data separated and segregated according to relevant data policies.
 </li>
 <li>
 Demonstrated ability to join a complex global team, collaborate crossfunctionally (data scientists, platform engineers, business stakeholders), and take ownership of major components of the data platform ecosystem and develop data ready tools to support their job.
 </li>
 <li>
 Be up-to-date with the latest tech trends in the big-data space and recommend them as needed.
 </li>
 <li>
 Identify, investigate, and resolve data discrepancies by finding the root cause of issues; work with partners across various cross-functional teams to prevent future occurrences.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Overall 4+ years of hands-on experience in computer/software engineering with majority in big data engineering.
 </li>
 <li>
 4+ years of strong Python or Scala programming skills (Core Python and PySpark) including hands-on experience creating and supporting UDFs and modules like pytest.
 </li>
 <li>
 4+ years of experience with building and optimizing &lsquo;big data&rsquo; pipelines, architectures, and data sets. Familiarity with data pipeline and workflow management tools (e.g., Airflow, DBT, Kafka).
 </li>
 <li>
 4+ years of hands-on experience on developing on Spark in a production environment. Expertise on parallel execution, deciding resources and different modes of executing jobs is required.
 </li>
 <li>
 4+ years of experience using Hive (on Spark), Yarn (logs, DAG flow diagrams), Sqoop. Proficiency bucketing, partitioning, tuning and handling different file formats (ORC, PARQUET &amp; AVRO).
 </li>
 <li>
 4+ years of experience using Transact SQL (e.g., MS SQ Server, MySQL), No-SQL and GraphQL.
 </li>
 <li>
 Strong experience implementing solutions on Snowflake
 </li>
 <li>
 Experience with data quality and validation frameworks, especially Great Expectations for automated testing.
 </li>
 <li>
 Strong understanding and use of Swagger/OpenAPI for designing, documenting, and testing RESTful APIs.
 </li>
 <li>
 Experience in deployment, maintenance, and administration tasks related to Cloud (AWS, Azure Preferred), OpenStack, Docker, Kafka and Kubernetes. Familiarity with CI/CD pipelines for data pipeline automation and deployment (Jenkins, GitLab CI, Azure DevOps)
 </li>
 <li>
 Experience with data governance, metadata management, and data lineage using tools like Axon and Unity Catalog. Expertise in managing business glossaries, data access control, auditing, and ensuring centralized governance across data assets in both cloud and hybrid environments.
 </li>
 <li>
 Hands-on experience with Databricks, including notebooks, workflows, and ML integrations.
 </li>
 <li>
 Experience with working with global teams across different time zones
 </li>
 <li>
 Plus - Experience with Machine Learning and Artificial Intelligence
 </li>
 <li>
 Plus - Experience with Generative Artificial Intelligence
 
 
 </li>
 </ul>
 For New York, NY Only the salary range for this position is USD$132,500.00 - USD$162,000.00 . Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, leave benefits, and retirement benefits. BlackRock operates a pay-for-performance compensation philosophy and your total compensation may vary based on role, location, and firm, department and individual performance.
 
 
 
 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&rsquo;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 &ndash; 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.
 
 
 
 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&rsquo;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 &ndash; the one we make in our employees. It&rsquo;s why we&rsquo;re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.
 
 
 For additional information on BlackRock, please visit @blackrock | Twitter: @blackrock | LinkedIn: www.linkedin.com/company/blackrock
 
 
 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&rsquo;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.
</div>

Data Engineer, Associate

G-III Apparel Group

<div>
 
 
 Data Engineer
 
 
 
 G-III Apparel Group
 
 
 
 
 
 
 Department:
 
 Data &amp; Analytics
 
 
 
 Reporting To:
 
 VP Data Insights
 
 
 
 Location (On-Site):
 
 New York, NY - Fashion District
 
 
 
 
 
 
 About G-III Apparel Group, Ltd. | www.g-iii.com
 
 
 
 G-III Apparel Group is a global leader in design, sourcing, manufacturing, distribution, and marketing. We bring excitement and confidence to customers through the fashion we create. With more than 30 owned and licensed brands, including some of the most recognized names in global fashion, our success is driven by entrepreneurial thinking, operational excellence, and strong industry partnerships.
 
 
 
 
 
 
 Position Summary
 
 
 
 The Data Engineer is responsible for building and maintaining the data infrastructure that supports analytics, reporting, and operational decision-making across the organization. Reporting to the VP of Data Insights, this role develops scalable data pipelines and reliable datasets used by internal teams, business partners, and analytics platforms. The Data Engineer will work closely with data scientists, engineers, and business stakeholders to ensure high-quality, accessible data that supports the company&rsquo;s broader data and analytics strategy.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, build and maintain scalable ETL/ELT pipelines to ingest, transform, and deliver data across enterprise systems
 </li>
 <li>
 Prepare, cleanse, and structure large datasets to support analytical modeling, reporting, and operational decision-making
 </li>
 <li>
 Implement data quality frameworks, validation rules, and monitoring systems to ensure data integrity and accuracy
 </li>
 <li>
 Partner with data scientists and analytics teams to support feature engineering and data preparation for quantitative analysis
 </li>
 <li>
 Work with engineering teams to implement automated anomaly detection and data monitoring solutions
 </li>
 <li>
 Serve as a subject-matter expert on internal datasets, including definitions, lineage, and quality standards
 </li>
 <li>
 Collaborate with product owners, business stakeholders, and systems teams to deliver reliable data products and services
 </li>
 <li>
 Design and maintain data models, data warehouses, and modern data architectures such as data lakes and data marts
 </li>
 <li>
 Contribute to the development of data governance standards, data documentation, and metadata management practices
 </li>
 <li>
 Support continuous improvement of the data platform through automation, testing, and performance optimization
 </li>
 <li>
 Ensure timely and reliable data delivery to support operational and strategic business needs
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 
 
 Required:
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Engineering, Mathematics, Statistics, Economics, or equivalent practical experience
 </li>
 <li>
 3+ years of experience in data engineering or a similar data infrastructure role
 </li>
 <li>
 Strong proficiency in SQL and experience working with large relational datasets
 </li>
 <li>
 Programming experience in Python (including data processing libraries such as PySpark)
 </li>
 <li>
 Experience designing and implementing ETL/ELT pipelines and data integration workflows
 </li>
 <li>
 Experience with modern cloud platforms such as AWS, Azure, or GCP
 </li>
 <li>
 Working knowledge of data warehousing concepts, including data lakes, operational data stores, and dimensional modeling
 </li>
 <li>
 Familiarity with modern data orchestration and transformation tools (e.g., Airflow, Databricks, Data Factory, or similar)
 </li>
 <li>
 Understanding of data modeling, data governance, and data quality best practices
 </li>
 <li>
 Experience working in collaborative engineering environments using Git, CI/CD pipelines, and automated testing frameworks
 </li>
 <li>
 Strong analytical and problem-solving skills with the ability to communicate technical concepts clearly to both technical and non-technical audiences
 </li>
 <li>
 Ability to manage multiple priorities and deliver high-quality work in a fast-paced environment
 </li>
 </ul>
 
 
 
 
 
 Preferred:
 
 
 <ul>
 <li>
 Experience building scalable pipelines using Spark or distributed processing frameworks
 </li>
 <li>
 Familiarity with Azure data services such as Azure Data Factory, Microsoft Fabric, Synapse or Databricks
 </li>
 <li>
 Exposure to streaming or real-time data architectures
 </li>
 <li>
 Experience implementing data quality frameworks and governance programs
 </li>
 <li>
 Familiarity with business intelligence tools such as Power BI
 </li>
 <li>
 Prior experience in retail, fashion, or consumer products industries
 </li>
 <li>
 Experience leveraging AI-assisted development tools (e.g., Copilot, GPT-based coding assistants) to improve engineering productivity
 </li>
 <li>
 Master&rsquo;s degree in a related quantitative or technical field
 </li>
 </ul>
 
 
 
 
 
 What We Offer
 
 
 <ul>
 <li>
 Competitive base salary and performance-based incentives
 </li>
 <li>
 Comprehensive medical, dental, and vision benefits
 </li>
 <li>
 401(k) with company match
 </li>
 <li>
 Paid time off, holidays, and company-sponsored wellness benefits
 </li>
 <li>
 Employee discounts across G-III brands
 </li>
 <li>
 A collaborative, entrepreneurial work environment with career growth opportunities
 </li>
 </ul>
 
 
 
 
 
 Compensation
 
 
 
 
 Salary Range: $120,000 &ndash; $135,000 base (commensurate with experience)
 
 
 
 
 Please note that the foregoing compensation information is a good-faith assessment associated with this position only and is provided pursuant to the New York City Salary Transparency Law.
 
 
 
 
 
 
 
 G-III&rsquo;s owned brands include DKNY, Karl Lagerfeld Paris, Donna Karan, Vilebrequin, Sonia Rykiel, G.H. Bass, Bass Outdoor, Andrew Marc, Eliza J., G-III Sports and more. G-III holds licenses for Calvin Klein, Tommy Hilfiger, Cole Haan, Dockers, Guess?, Kenneth Cole, Levi&rsquo;s, Vince Camuto, Margaritaville, and others. The company also operates retail stores for DKNY, Karl Lagerfeld Paris, and Donna Karan.
 
 
</div>

Exert Infotech LLC

<div>
 
 📢 Hiring: Data Engineer (Entry-Level) &ndash; USA 🇺🇸
 
 
 
 🎓 Open to Dec 2025 &amp; May Graduates | Visa Sponsorship Available
 
 
 
 We are actively looking for
 
 motivated and detail-oriented Data Engineer graduates
 
 to join our growing team in the United States. If you are passionate about data, cloud technologies, and building scalable pipelines &mdash; this is a great opportunity to kickstart your career.
 
 
 🔹 Role: Data Engineer (Entry-Level)
 
 
 📍 Location: United States (Onsite / Hybrid / Remote options available)
 
 
 🎓 Eligibility: Graduating in
 
 Dec 2025 or May 2026
 
 
 
 💼 Job Type: Full-time
 
 
 🌍 Work Authorization:
 
 OPT / CPT / STEM OPT / GC/ US Citizen
 
 
 
 🔧 Key Responsibilities:
 
 <ul>
 <li>
 Design, build, and maintain scalable
 
 data pipelines
 
 </li>
 <li>
 Work with large datasets using
 
 SQL, Python, or Spark
 
 </li>
 <li>
 Support
 
 ETL/ELT processes
 
 and data integration
 </li>
 <li>
 Collaborate with data analysts and business teams
 </li>
 <li>
 Ensure
 
 data quality, governance, and performance optimization
 
 </li>
 </ul>
 
 🛠️ Required Skills:
 
 <ul>
 <li>
 Strong knowledge of
 
 SQL &amp; Python
 
 </li>
 <li>
 Understanding of
 
 Data Structures &amp; Algorithms
 
 </li>
 <li>
 Familiarity with
 
 cloud platforms
 
 (AWS / Azure / GCP)
 </li>
 <li>
 Exposure to tools like
 
 Apache Spark, Hadoop, Snowflake
 
 </li>
 <li>
 Basic understanding of
 
 data warehousing concepts
 
 </li>
 </ul>
 
 ⭐ Preferred Qualifications:
 
 <ul>
 <li>
 Internship/project experience in data engineering or analytics
 </li>
 <li>
 Knowledge of
 
 Airflow, Kafka, or DBT
 
 </li>
 <li>
 Experience with
 
 real-time data processing
 
 </li>
 </ul>
 
 
</div>

Jr Data Engineer

NTT DATA North America

<div>
 
 At NTT DATA, we know that with the right people on board, anything is possible. The quality, integrity, and commitment of our employees have been key factors in our company's growth and market presence. By hiring the best people and helping them grow both professionally and personally, we ensure a bright future for NTT DATA and for the people who work here.
 
 For more than 25 years, NTT DATA Services have focused on impacting the core of your business operations with industry-leading outsourcing services and automation. With our industry-specific platforms, we deliver continuous value addition, and innovation that will improve your business outcomes. Outsourcing is not just a method of gaining a one-time cost advantage, but an effective strategy for gaining and maintaining competitive advantages when executed as part of an overall sourcing strategy.
 
 
 NTT DATA's Client is seeking a Data Engineer for collaborative work with the client's technology and business staff day-to-day
 
 &bull; Codes, tests, debugs, implements, and documents complex global applications.
 
 &bull; Negotiate features and associated priorities and help the team and their customers reach consensus.
 
 &bull; Develops and/or leads the development of prototypes,
 
 &bull; Identify problem causality, business impact and root causes.
 
 &bull; Coming up with exact solutions for problems related to object identity and error handling.
 
 
 
 Skills required:
 
 
 &bull;
 
 Minimum 7+ years of work experience in building data pipelines using Python, PySpark, DJango.
 
 &bull; Should have hands on experience on the MLOp
 
 s.
 
 
 &bull; Hands-On experience in working with Python and related packages (like NumPy, pandas etc.) to load and scrap the data.
 
 &bull; Hands-on experience with at least one of the tools the Hadoop eco-system (HDFS, AWS Glue, MapReduce, Yarn, Hive, Pig, Impala, Spark, Kafka)
 
 .
 
 &bull; Working experience on Relational/Non-relational databases and familiarity with data model concepts
 
 &bull; Working exposure in blending as part of larger scrum team and understanding of related scrum ceremonies
 
 
 &bull; Working knowledge of Unix/Linux.
 
 
 
 
 Preferred:
 
 
 &bull; Knowledge of cloud platforms (e.g., AWS, Azure, GCP)
 
 
 About NTT DATA Services:
 
 
 NTT DATA Services is a recognized leader in IT and business services, including cloud, data and applications, headquartered in Texas. As part of NTT DATA, a $30 billion trusted global innovator with a combined global reach of over 80 countries, we help clients transform through business and technology consulting, industry and digital solutions, applications development and management, managed edge-to-cloud infrastructure services, BPO, systems integration and global data centers. We are committed to our clients' long-term success. Visit nttdata.com or LinkedIn to learn more.
 
 
 NTT DATA Services is an equal opportunity employer and considers all applicants without regarding to race, color, religion, citizenship, national origin, ancestry, age, sex, sexual orientation, gender identity, genetic information, physical or mental disability, veteran or marital status, or any other characteristic protected by law. We are committed to creating a diverse and inclusive environment for all employees. If you need assistance or an accommodation due to a disability, please inform your recruiter so that we may connect you with the appropriate team.
 
 
 Where required by law, NTT DATA provides a reasonable range of compensation for specific roles. The starting hourly range for this remote role is
 
 ($70-$79/hourly )
 
 . This range reflects the minimum and maximum target compensation for the position across all US locations. Actual compensation will depend on several factors, including the candidate's actual work location, relevant experience, technical skills, and other qualifications.
 
 
 This position is eligible for company benefits that will depend on the nature of the role offered. Company benefits may include medical, dental, and vision insurance, flexible spending or health savings account, life, and AD&amp;D insurance, short-and long-term disability coverage, paid time off, employee assistance, participation in a 401k program with company match, and additional voluntary or legally required benefits.
 
 
</div>

Explore 686+ Data pipeline engineer in New York this May. Find roles across top companies and apply now to boost your career.

686 data pipeline engineer jobs In New York

Senior Associate, Analytics Data Engineer

Data Engineer

Data Engineer

Data Engineer, Associate

Data Engineer

Jr Data Engineer

Data Engineer