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Airflow Dag Jobs (NOW HIRING)

PetsApp

Senior Backend/Infra Engineer

Boston, MA · On-site

$170K - $180K/yr

Backend - Django, Airflow DAG, Postgres * Infrastructure - Docker, ECS, RDS, Lambda, Airflow, Pulumi or Terraform, Github Action, Prometheus/Grafana * CRM - Hubspot * Others - Retool, Google ...

Intraedge

Python Software Developer

Phoenix, AZ · On-site

$50 - $68.75/hr

... Airflow (DAG design and orchestration) · Strong experience with data ingestion and pipeline development · Experience with BigQuery (BQ), Bigtable, and CloudSQL · Experience designing Star and ...

Gigatec Engineering

UX Software Engineer

Annapolis, MD · On-site

$165K - $265K/yr

Experience using Apache Airflow (DAG design, scheduling, operators, sensors) to orchestrate, schedule, and monitor complex workflows * Experience with SQL technologies such as MySQL, MariaDB, and ...

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Airflow Dag information

What is an Airflow DAG?

An Airflow DAG, or Directed Acyclic Graph, is a collection of tasks organized in a way that reflects their dependencies and execution order in Apache Airflow. It defines how and when tasks should run, ensuring a workflow's steps are executed in the correct sequence without cycles. DAGs are written in Python and are used to automate, schedule, and monitor complex data pipelines or workflows. By using Airflow DAGs, teams can manage and track their data processing jobs efficiently.

What are the key skills and qualifications needed to thrive as an Airflow DAG developer, and why are they important?

To excel as an Airflow DAG Developer, you need strong Python programming skills, experience with workflow orchestration, and a solid foundation in data engineering principles. Familiarity with Apache Airflow, version control systems like Git, and cloud platforms such as AWS or GCP is commonly required. Effective problem-solving, attention to detail, and clear communication are essential soft skills that set top performers apart. Mastery of these areas ensures efficient, reliable data pipeline development and smooth collaboration with data teams.

What are some common challenges faced when managing and maintaining Apache Airflow DAGs in a production environment?

One of the main challenges when working with Apache Airflow DAGs is ensuring reliable scheduling and execution, especially as the number and complexity of workflows grow. Issues like task dependencies, resource contention, and handling failures can arise, requiring careful design and monitoring. Additionally, managing code versioning and deployment of DAGs across development and production environments can be tricky, often necessitating robust CI/CD pipelines and clear collaboration between data engineers and DevOps teams. Regularly reviewing and optimizing DAG performance is also important to avoid bottlenecks and ensure scalability.

What is the difference between Airflow Dag vs Airflow Operator?

AspectAirflow DagAirflow Operator
DefinitionA collection of tasks organized to define a workflow in Apache Airflow.A single task or unit of work within a DAG, responsible for executing specific actions.
FunctionOrchestrates and schedules multiple tasks to run in a sequence or parallel.Performs a specific operation, such as data transfer or transformation.
UsageUsed to define entire workflows in Airflow.Used within DAGs to perform individual steps.
Credentials/CertificationsRequires knowledge of Python, Airflow setup, and scheduling concepts.Requires understanding of task-specific operations and Airflow operators.

In summary, an Airflow DAG is a blueprint for a workflow, organizing multiple tasks, while an Airflow Operator is a single task that performs a specific function within that workflow. Both are essential for building and managing data pipelines in Airflow.

Infographic showing various Airflow Dag job openings in the United States as of September 2026, with employment types broken down into 95% Full Time, 1% Part Time, and 4% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution.

Lead Software Engineer - Full Stack

San Francisco, CA • On-site

JPMorgan Chase & Co.
Finance and Insurance • 10K+ employees
Learn more about JPMorgan Chase & Co.external

$156K - $215K/yr

Full-time

Medical, Retirement

Re-posted 9 days ago

JPMorgan Chase & Co. rating

7.9

Company rating: 7.9 out of 10

Based on 500 frontline employees who took The Breakroom Quiz

Job description


We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Lead Software Engineer - Full Stack at JPMorgan Chase within the Enterprise Technology - Network Services Team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. This role is hands-on and suited for seasoned full stack engineers who can own end-to-end delivery-from system design through implementation, deployment on Kubernetes, and production operations (monitoring, troubleshooting, and performance tuning).
Job responsibilities
  • Executes creative software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems
  • Owns end-to-end full stack delivery across; Frontend (React/TypeScript), Backend (Python services), Data/Workflow Services (Apache Airflow - DAG design) and Database (CockroachDB - data modeling)
  • Designs and delivers scalable, highly available services and user experiences for large-scale applications; drives architecture decisions that improve throughput, latency, reliability, and operability
  • Builds and maintains cloud-native deployments on Kubernetes, including configuration, scaling strategies, and operational readiness (health checks, rollouts, rollback strategies, capacity considerations)
  • Drives monitoring, observability, and performance tuning across the stack using tools such as Splunk and Grafana (and related logging/metrics/tracing patterns); leads root-cause analysis and remediation
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
  • Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

Required qualifications, capabilities, and skills
  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Demonstrated full stack engineering capability (frontend + backend) and ability to deliver independently across the SDLC
  • Strong proficiency in Python and experience building microservices and automation frameworks; working knowledge of JavaScript for tooling/UI/integrations and strong React experience building production-grade web applications (performance, usability, maintainability)
  • Hands-on experience deploying and operating workloads on Kubernetes (deployments, services, scaling, configuration, troubleshooting) and hands-on experience with API gateways, Kafka, and event-driven architectures
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
  • Experience with workflow orchestration using Apache Airflow (DAG authoring, dependency design, failure handling, and operational support) and experience with distributed databases / SQL data stores; working knowledge of CockroachDB or similar distributed SQL systems (schema design, query performance, reliability considerations)
  • Proven ability to support observability and operations, including log/metric-based troubleshooting and performance tuning using tools such as Splunk and Grafana
  • Experience developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
  • Experience with CI/CD, automated testing (unit/integration), observability (logs/metrics/traces), and application security (authn/authz basics, secrets handling, dependency scanning)
  • Demonstrated technical leadership as a senior IC (leading designs, driving delivery, and influencing across teams)

Preferred qualifications, capabilities, and skills
  • Experience designing and delivering high-scale systems (high throughput/low latency, multi-service architectures, scaling and capacity planning)
  • Strong experience in production readiness practices (SLOs/SLIs, error budgets, alert tuning, runbooks, incident management)
  • Experience with agentic AI frameworks and model-to-tool integration patterns (prompt/tool design, structured outputs, evaluation/monitoring)
  • Experience building robust CI/CD pipelines for Kubernetes deployments (testing strategies, automated quality gates, safe delivery patterns)
  • Experience implementing distributed system resiliency patterns (rate limiting, retries/backoff, circuit breakers, idempotency) and experience with event-driven architectures and workflow engines
  • Familiarity with secure software delivery practices (threat modeling, secrets management, least privilege, supply chain controls)

FEDERAL DEPOSIT INSURANCE ACT:
This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase's review of criminal conviction history, including pretrial diversions or program entries.
About Us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About the Team
Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.

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