Senior Developer(Senior Data Science Engineer)

At Arctic Wolf, you won’t just watch the cybersecurity industry evolve – you'll help lead the change. Our global Pack is made up of people who thrive on solving hard problems, moving fast, and building technology that protects organizations around the world. We’re proud to be recognized by Forbes, CNBC, Fortune, CRN, Bartner Peer Insights and IDC MarketScape – but what matters most is the work behind it: delivering real outcomes for customers through award winning innovation like our Aurora Platform.

If you’re looking for meaningful work, smart teammates and the chance to make a real impact in a high-growth company that’s redefining security operations, Arctic Wolf is the right place for you

• Our mission is simple: End Cyber Risk. We’re looking for a/an

Senior Developer

(

Senior Data Science Engineer

)

​

to be part of making this/that happen.

Position Overview and Objective

We are looking for an exceptional

Senior Developer

(

Senior Data Science Engineer

)skilled at deriving deep insights from large-scale datasets and enabling data-driven decisions across the organization. You will uncover patterns, detect anomalies, and identify inefficiencies within complex systems. With strong AWS expertise—and ideally, exposure to Databricks—you will help optimize our data infrastructure, enhance analytical workflows, and propose scalable architectural improvements. Your recommendations will be grounded in robust system design, cloud engineering best practices, and advanced analytics.

Responsibilities

• Analyze complex, large-scale datasets to uncover trends, patterns, anomalies, and strategic insights.
• Design, build, and optimize data pipelines, ETL/ELT flows, and analytical models using AWS services—and optionally Databricks.
• Identify inefficiencies, bottlenecks, and data quality issues; recommend scalable, long-term solutions.
• Implement and tune distributed data processing workflows (Spark, EMR, Glue, or Databricks).
• Leverage analytics and statistical techniques to build models, derive insights, and support predictive capabilities.
• Collaborate with engineering, product, and business teams to define and deliver data-driven solutions.
• Perform root-cause analyses on data pipeline failures and optimize infrastructure for reliability and cost-effectiveness.
• Develop dashboards, tools, or automation that improve visibility and decision-making.
• Document system architecture, analytical methodologies, and data engineering best practices.
• Stay up-to-date with modern data platforms (including Databricks), cloud technologies, and scalable data design patterns.

Experience & Requirements

• You have 5–10 years of experience in data analysis, engineering, or related data-driven disciplines.
• You have strong hands-on expertise across the AWS ecosystem, with a solid understanding of data architecture and cloud primitives.
• You are highly proficient in Python and capable of building scalable data pipelines, transformations, and analysis workflows.
• You bring 3–5 years of experience in data science or analytics, including statistical analysis and applied ML techniques.
• You have driven industry insights, cost optimization initiatives, and operational improvements using data.
• You can detect anomalies, identify systemic inefficiencies, and articulate the “why” behind patterns in large datasets.
• You understand system design, distributed architectures, and can propose improvements for performance, scalability, and cost.
• Exposure to Databricks is a strong advantage, especially in building or optimizing data workflows and collaborative analytics

• Nice To Have:

• Advanced degree in Computer Science, Data Science, Engineering, Statistics, or related field.
• Hands-on experience with distributed computing frameworks such as Spark, EMR, Glue, or Databricks (strong plus).
• Exposure to the Databricks Lakehouse platform, including notebooks, Unity Catalog, or Delta Lake workflows.
• Strong SQL skills with experience in query tuning and performance optimization.
• Familiarity with AWS cost-optimization strategies and cloud monitoring tools.
• Understanding of data orchestration frameworks (Airflow, Step Functions) and event-driven architectures.
• Experience deploying ML models at scale or working with ML Ops toolchains.
• Knowledge of containerization (Docker, ECS, EKS) or serverless technologies.
• Excellent communication skills with the ability to translate complex technical insights into clear, actionable recommendations.

On-Camera Policy

To support a fair, transparent, and engaging interview experience, candidates interviewing remotely are expected to be on camera during all video interviews. Being on camera fosters authentic connection, improves communication, and allows for full engagement from both candidates and interviewers. We understand that technical, bandwidth, or location-related challenges may occasionally prevent video use. If this applies, candidates are required to notify us in advance so we can explore appropriate accommodations.

About Arctic Wolf

At Arctic Wolf, we foster a collaborative and inclusive work environment that thrives on diversity of thought, background, and culture. This is reflected in our multiple awards, including Top Workplace USA (2021-2025), Best Places to Work – USA (2021-2025), Great Place to Work – Canada (2021-2024), Great Place to Work – UK (2024-2026), and Kununu Top Company – Germany (2024-2026). Our commitment to bold growth and shaping the future of security operations is matched by our dedication to customer satisfaction, with over 10,000 customers worldwide and more than 2,000 channel partners globally. As we continue to expand globally and enhance our technology, Arctic Wolf remains the most trusted name in the industry.

Our Values

Arctic Wolf recognizes that success comes from delighting our customers, so we work together to ensure that happens every day. We believe in diversity and inclusion, and truly value the unique qualities and unique perspectives all employees bring to the organization. And we appreciate that—by protecting people’s and organizations’ sensitive data and seeking to end cyber risk— we get to work in an industry that is fundamental to the greater good.

We celebrate unique perspectives by creating a platform for all voices to be heard through our Pack Unity program. We encourage all employees to join or create a new alliance. See more about our Pack Unity here.

We also believe and practice corporate responsibility, and have recently joined the Pledge 1% Movement, ensuring that we continue to give back to our community. We know that through our mission to End Cyber Risk we will continue to engage and give back to our communities.

All

India

wolves receive compelling compensation and benefits packages, including:

• Equity for all employees
• Flexible annual leave, paid holidays and volunteer days
• Training and career development programs
• Comprehensive private benefits plan including medical insurance for you and your family, life insurance (3x compensation), and personal accident insurance.
• Fertility support and paid parental leave

Arctic Wolf is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, provincial, or local law. Arctic Wolf is committed to fostering a welcoming, accessible, respectful, and inclusive environment ensuring equal access and participation for people with disabilities. As such, we strive to make our entire experience as accessible as possible and provide accommodations as required for candidates and employees with disabilities and/or other specific needs where possible. Please let us know if you require any accommodation by emailing [email protected]. View our Hiring Page to learn more about our application process.

Security Requirements

• Conducts duties and responsibilities in accordance with AWN’s Information Security policies, standards, processes, and controls to protect the confidentiality, integrity and availability of AWN business information (in accordance with our employee handbook and corporate policies).
• Background checks are required for this position.
• This position may require access to information protected under U.S. export control laws and regulations, including the Export Administration Regulations (“EAR”). Please note that, if applicable, an offer for employment will be conditioned on authorization to receive software or technology controlled under these U.S. export control laws and regulations.

• Advanced degree in Computer Science, Data Science, Engineering, Statistics, or related field.
• Hands-on experience with distributed computing frameworks such as Spark, EMR, Glue, or Databricks (strong plus).
• Exposure to the Databricks Lakehouse platform, including notebooks, Unity Catalog, or Delta Lake workflows.
• Strong SQL skills with experience in query tuning and performance optimization.
• Familiarity with AWS cost-optimization strategies and cloud monitoring tools.
• Understanding of data orchestration frameworks (Airflow, Step Functions) and event-driven architectures.
• Experience deploying ML models at scale or working with ML Ops toolchains.
• Knowledge of containerization (Docker, ECS, EKS) or serverless technologies.
• Excellent communication skills with the ability to translate complex technical insights into clear, actionable recommendations.