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Data Engineer Airflow Jobs in Merrick, NY (NOW HIRING)

Bright Mind Solutions LLC

GCP Data Engineer

New York, NY · On-site

$50 - $55/hr

Orchestrate workflows with Cloud Composer (Airflow) * Lead data migrations from Snowflake/AWS to ... GCP Certification (Professional Data Engineer required) * 5+ years in data engineering with strong ...

Kanak Elite Services Inc

Data Engineer

New York, NY · On-site

$125K - $150K/yr

Data Engineer Location: NYC, NY & Alpharetta, GA (Locals preferred & can submit from nearby ... Python * - Spark, Hive, Airflow Preferred Skills: * - Cloud data platforms (AWS/GCP/Azure ...

Courier Health

Data Engineer

New York, NY · On-site

$120K - $150K/yr

About the Team You'll join an early and growing data engineering team that's shaping the ... Estuary Flow, Debezium/Kafka, Airflow), a cloud data warehouse (ex. Redshift), a BI tool (ex. Sigma ...

Arlo

Data Engineer

Manhattan, NY · On-site

$126K - $151K/yr

They are seeking a Data Engineer to build and maintain data pipelines, ensuring reliable data ... or Airflow, ensuring reliable scheduling, retries, and alerting • Build monitoring and alerting ...

Donato Technologies, Inc

Data Engineer

New York, NY · On-site

$125K - $150K/yr

Job Title: Sr Data engineer Location : NYC Experience - 8+ 5 Days Onsite Look for only New york and ... Proficiency in atleast one scheduling/orchestration tools (preferably Airflow, alternatively AWS ...

Donato Technologies, Inc

Data Engineer

New York, NY · On-site

$125K - $150K/yr

Sr. Data Engineer New York (35 Miles) Experience: 10+ Years :- Required Skills: * 1.Proficiency in ... Proficiency in atleast one scheduling/orchestration tools (preferably Airflow, alternatively AWS ...

Keystone

Data Engineer

Manhattan, NY · On-site

$126K - $151K/yr

The Data Engineer will lead the design and implementation of scalable data workflows and ... Airflow, dbt, Spark, or equivalent). • Design data models and storage systems optimized for ...

Courier Health

Data Engineer

New York, NY · On-site

$120K - $150K/yr

About the Team You'll join an early and growing data engineering team that's shaping the ... Estuary Flow, Debezium/Kafka, Airflow), a cloud data warehouse (ex. Redshift), a BI tool (ex. Sigma ...

Long Finch Technologies

Sr. GCP Data Engineer

Brooklyn, NY · On-site

$117K - $140K/yr

Role Summary This is Client-Facing, Onshore role, Senior GCP Data Engineering Lead will be ... The role requires strong hands-on expertise in BigQuery, Airflow/Cloud Composer, Python development ...

New

Long Finch Technologies

Sr. GCP Data Engineer

New York, NY · On-site

$125K - $150K/yr

Role Summary This is Client-Facing, Onshore role, Senior GCP Data Engineering Lead will be ... The role requires strong hands-on expertise in BigQuery, Airflow/Cloud Composer, Python development ...

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Showing results 1-20

All JobsData Engineer Airflow JobsData Engineer Airflow Jobs in Merrick, NY

Data Engineer Airflow information

See Merrick, NY salary details

$45.6K

$132.8K

$181.8K

How much do data engineer airflow jobs pay per year?

As of Aug 28, 2026, the average yearly pay for data engineer airflow in Merrick, NY is $132,824.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,200.00 and $140,800.00 per year, depending on experience, location, and employer.

What does a data engineer specializing in Airflow do?

A Data Engineer specializing in Airflow is responsible for designing, building, and maintaining data pipelines using Apache Airflow, an open-source workflow orchestration tool. Their main job is to automate, schedule, and monitor complex data workflows, ensuring data moves reliably between systems and is processed efficiently. They often collaborate with data scientists, analysts, and other engineers to make sure that data is accessible, accurate, and up to date for business needs. Expertise in Airflow helps streamline data operations, optimize performance, and improve data pipeline reliability.

How does a data engineer specializing in Airflow typically collaborate with data scientists and analysts?

Data Engineers working with Airflow play a crucial role in enabling data scientists and analysts to access reliable, up-to-date data. They design and maintain ETL pipelines that automate data movement and transformation, ensuring data is clean and available for analysis. Collaboration often involves gathering requirements, troubleshooting pipeline issues, and optimizing data workflows to meet the needs of downstream users. Effective communication and documentation are essential, as data engineers must align technical solutions with the analytical goals of the broader team.

What are the key skills and qualifications needed to thrive as a data engineer specializing in Airflow, and why are they important?

To thrive as a Data Engineer with an Airflow focus, you need strong programming skills in Python, expertise in data pipeline design, and experience with distributed systems, often supported by a degree in computer science or a related field. Familiarity with Apache Airflow, cloud platforms (like AWS or GCP), and database technologies, as well as certifications in cloud data engineering, are typically required. Outstanding problem-solving, attention to detail, and effective communication help you collaborate on complex data workflows and troubleshoot issues efficiently. These skills ensure robust, scalable, and reliable data infrastructure, enabling organizations to make data-driven decisions with confidence.

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

AspectData Engineer AirflowData Engineer
Primary FocusWorkflow orchestration and pipeline automation using AirflowData collection, storage, transformation, and pipeline development
Required SkillsPython, Airflow, ETL processes, cloud platformsSQL, Python, ETL, data modeling, cloud services
Work EnvironmentData teams, cloud environments, automation pipelinesData warehouses, big data platforms, cloud infrastructure
CertificationsAirflow certifications, Python, cloud certificationsSQL, cloud certifications, data engineering certifications

While both roles involve data pipeline work, Data Engineer Airflow specializes in designing and managing workflows with Airflow, focusing on automation and orchestration. In contrast, Data Engineer has a broader scope, including data storage, transformation, and pipeline development across various tools and platforms.

What cities near Merrick, NY are hiring for Data Engineer Airflow jobs?

Cities near Merrick, NY with the most Data Engineer Airflow job openings:

Data Engineer Airflow jobs near you
Infographic showing various Data Engineer Airflow job openings in Merrick, NY as of July 2026, with employment types broken down into 2% Locum Tenens, 87% Full Time, 7% Part Time, and 4% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $132,824 per year, or $63.9 per hour.

Senior Workflow Orchestration Engineer (Airflow & Scheduling Platforms)

Benton Partners

Manhattan, NY • On-site

$140 - $210/hr

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Senior Workflow Orchestration Engineer (Airflow & Scheduling Platforms)
  • NY or Chi, NYC
About therole

We'reseeking a seasoned engineer to design,operate, and scale our workflow orchestration platform with a primary focus on Apache Airflow.You'llown the Airflow control plane and developer experience end-to-end-architecture, automation, security, observability, and reliability-while also evaluating andoperatingcomplementary schedulers whereappropriate.You'llbuild automation infrastructure and partner across data, trading, and engineering teams to deliver mission-critical pipelines at scale.

Whatyou'lldo
  • Architect, deploy, andoperateproduction-grade Airflow on Kubernetes including all components and user application dependencies, with focus on upgrades, capacity planning, HA, security, and performance tuning
  • Operate a multi-scheduler ecosystem:determinewhen to use Airflow, distributed compute schedulers, or lightweight task runners based on workload requirements; provide unified developer experience across schedulers
  • Build automation infrastructure: Terraform modules and Helm charts withGitOps-driven CI/CD for environment provisioning, upgrades, and zero-downtime rollouts
  • Standardize the developer experience: DAG repo templates, shared operator libraries, connection and secrets management, dependency packaging, code ownership, linting, unit testing, and pre-commit hooks
  • Implement comprehensive observability: metrics collection, dashboards, distributed tracing, SLA/latency monitoring, intelligent alerting, and runbook automation
  • Enable resilient workflow patterns: build idempotency frameworks, retry/backoff strategies, deferrable operators and sensors, dynamic task mapping, and data-aware scheduling
  • Ensure reliability at enterprise scale: architect and tune resource allocation (pools, queues, concurrency limits) to support high-throughput workloads-optimizelarge-scale backfill strategies; develop comprehensive runbooks and lead incident response/postmortems
  • Partner with teams across the organization to provide enablement, documentation, and self-service tooling
  • Mentor engineers, contribute to platform roadmap and technical standards, and drive engineering best practices
Required qualifications
  • 5-8+ years building/operating data or platform systems; 3+ years running Airflow in production at scale (hundreds-thousands DAGs and high task throughput).
  • Deep Airflowexpertise: DAG design and testing, idempotency, deferrable operators/sensors, dynamic task mapping, task groups, datasets, pools/queues, SLAs, retries/backfills, cross-DAG dependencies.
  • Strong Kubernetes experience running Airflow and supporting services: Helm, autoscaling, node/pod tuning, topology spread, network policies, PDBs, and blue/green or canary strategies.
  • Automation-first mindset: Terraform, Helm,GitOps(Argo CD/Flux), and CI/CD for platform lifecycle; policy-as-code (OPA/Gatekeeper/Conftest) for DAG, connection, andsecretschanges.
  • Proficiencyin Python for authoring operators/hooks/utilities; solid Bash; familiarity with Go or Java is a plus.
  • Observability and SRE practices: Prometheus/Grafana/StatsD, centralized logging, alert design, capacity/throughput modeling, performance tuning.
  • Data platform experience with at least one major cloud (AWS/Azure/GCP) and systems like Snowflake/BigQuery/Redshift, Databricks/Spark, EMR/Dataproc; strong grasp of IAM, VPC networking, and storage (S3/GCS/ADLS).
  • Security/compliance: SSO/OIDC, RBAC,secretsmanagement (Vault/Secrets Manager), auditing, least-privilege connection management, and change control.
  • Proven incident leadership, runbook creation, and platform roadmap execution; excellent cross-functional communication.
Nice to have
  • Experience operating alternative orchestrators (Prefect 2.x,Dagster, Argo Workflows, AWS Step Functions) and leading migrations to/from Airflow.
  • OpenLineage/Marquez adoption; Great Expectations or other data quality frameworks; data contracts.
  • Cost optimization and capacity planning for schedulers and workers; spot instance strategies.
  • Multi-region HA/DR for Airflow metadata DB; backup/restore and disaster drills.
  • Building internal developer platforms/portals (e.g., Backstage) for self-service pipelines.
  • Contributions to Apache Airflow or provider packages; familiarity with recent AIPs/Airflow 2.7+ features.
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