Director - Data Engineering

Join our India Tech Hub – Be among the first hires!

Kobie, a 35-year veteran of the loyalty industry, a multi-year Forrester Leader, and USA Top Workplace is expanding its global footprint by establishing a Tech Hub in India. Kobie partners with global brands to build deep connections with their customers through personalized, data-driven loyalty experiences and has a mission of growing enterprise value through loyalty. The Tech Hub will serve as a Global Capabilities Center for a broad range of technology roles, and this is your chance to play a pivotal role in shaping our presence in India. Join us as we continue to lead in loyalty, delivering innovative customer experiences for some of the world’s most recognized brands while working alongside some of the best and brightest in loyalty.

About the team and what we will build together

Kobie runs some of the largest loyalty programs in the world. We are building an internal agent platform on Dataiku that automates analyst workflows, surfaces insights from program data in Snowflake, and gives our teams an LLM-native way to work with complex loyalty logic.

We are seeking a hands-on, strategic Director of Data Engineering with deep technical expertise in cloud data platforms (Snowflake preferred; Azure Databricks or AWS Redshift), experience to lead a cross-functional team delivering robust, scalable data platforms and analytics solutions. This role combines technical leadership, process ownership, program management discipline, and a strong innovation mindset to accelerate data-driven decision-making across the enterprise.

How You’ll Make an Impact

Data engineering (Responsibilities & expectations):

Lead design and delivery of enterprise data platforms on Snowflake including data ingestion, storage architecture, consumption patterns, and cost optimization.

Own architecture decisions for large-scale batch and streaming data pipelines, Data modeling (star, snowflake, dimensional), and semantic layers to support BI, ML, and Analytics.

Ensure high standards for data quality, lineage, observability, schema evolution, and metadata management (catalogs, documentation).

Champion secure-by-design implementation: access control (roles/policies), dynamic data masking, encryption, and compliance with data governance and regulatory requirements.

Drive performance tuning and cost control measures for Snowflake (clustering, micro-partitions, materialized views, warehouse sizing, query profiling).

Hire, mentor, and grow a high-performing engineering organization: senior engineers, architects, data pipeline owners, and DevOps/Platform engineers.

Process (Standards, governance and operational excellence):

Define and enforce engineering best practices: CI/CD for data pipelines, Git-based workflows, code reviews, testing frameworks, and automated deployments for Snowflake objects.

Implement data lifecycle and cost governance policies (storage retention, data tiering, rightsizing compute, budget tracking).

Partner with Data Governance and Privacy teams to operationalize data classification, cataloging, and data stewardship workflows.

Implement a metrics-driven culture: define KPIs for platform reliability, pipeline throughput, query performance, and business adoption; run regular reviews and continuous improvement cycles.

Program management (Delivery, stakeholder engagement and scaling):

Own end-to-end program delivery for large, multi-team initiatives-set milestones, resource plans, risk registers, and communication cadences.

Coordinate cross-functional stakeholders including product, analytics, ML/AI, security, legal, and infrastructure to align roadmaps and priorities.

Manage portfolio trade-offs: technical debt vs. new features, cost vs. performance, central platform vs. team autonomy.

Drive capacity planning and resource allocation across multiple projects; balance short-term business needs with platform investments.

Provide transparent status reporting to senior leadership, present roadmaps, and translate technical trade-offs into business impact and ROI metrics.

Innovation (Strategy and value creation):

Define long-term data platform vision: cloud-native data patterns, data mesh/mesh-like designs, Lakehouse architectures (Delta Lake), semantic layers, and self-serve analytics.

Evaluate and incubate emerging technologies (vector DBs, streaming analytics, dbt/transform frameworks, generative AI augmentation for analytics) to accelerate analytics and ML value.

Promote experimentation: small, fast pilots to validate new tools/approaches and scale successful patterns across the organization.

Build partnerships with cloud providers and ecosystem vendors (Snowflake, Databricks, AWS) to leverage new features and cost optimizations.

Foster a culture of continuous learning: internal Tech Talks, architecture reviews, and knowledge sharing.

In your first 90 days

By the end of your first 90 days, you will have delivered at least one production-grade platform or process improvement end-to-end—examples include a Terraform-managed Snowflake networking and access environment, a hardened CI/CD pipeline for Snowflake objects and data pipelines, or a monitored Snowflake deployment pattern with automated cost and performance observability. You will be participating in the on-call rotation, have authored or enhanced at least one runbook or incident playbook for pipeline/platform operations, and be prepared with a prioritized recommendation for the next reliability and scalability investment (technical approach, estimated effort, and expected business impact)..

What you need to be successful

15+ years of experience in data engineering, with at least 5 years leading teams and large-scale data platform programs.

Hands-on expertise with Snowflake (preferred) or equivalent experience with Azure Databricks or AWS Redshift at scale (production data platforms, multi-tenant pipelines).

Deep understanding of cloud data architectures, data modeling, performance tuning, security, and cost management.

Proven program management skills running complex, cross-functional initiatives and delivering measurable business impact.

Strong people leadership: hiring, coaching, and building high-performing engineering teams.

Excellent communication and stakeholder management; comfortable presenting to senior executives.

Bachelor’s or Master’s in Computer Science, Engineering, or related field (or equivalent experience).

Bonus Skills:

Experience with data mesh, feature stores, or ML infrastructure.

Experience with dbt, Delta Lake, Kafka/Event Hubs, Airflow, or similar orchestration tools.

Familiarity with feature stores, MLOps, and GenAI/RAG integration patterns.

Certifications: SnowPro or equivalent, cloud provider certifications.

About Kobie

Named a Top Workplace in the USA and Top Remote Workplace, Kobie is where the best minds in loyalty come together, driven by passion and innovation. We’re always looking for talented individuals ready to join a collaborative, growth-focused culture.

As a trusted partner to some of the world’s most recognized brands, we are loyalty leaders, helping brands build lasting emotional connections with their consumers. We do this with a strategy-led technology approach that uncovers the truth behind what drives consumers on an emotional level.As we launch our India Tech Hub, we are excited to bring our award-winning culture to a new region - creating an environment where collaboration, flexibility, and career growth come together to build something truly special.

We are proud to be the only loyalty provider to be externally recognized for their culture. We believe people thrive when they feel valued, supported, and empowered to be their authentic selves. Our commitment to diversity, equity, and inclusion ensures every teammate has a voice and the opportunity to be heard.

Giving back is in our DNA at Kobie,through an annual fundraiser, charitable partnerships, and volunteer opportunities, we encourage our teammates to make a difference in their communities.

To support our teammates beyond just their careers, we offer highly competitive benefits, comprehensive health coverage, and well-being perks that support our teammates and their dependents. We understand the importance of time for life outside of work - recognizing public holidays,offering flexible time off, and prioritizing work-life balance.

As we into India, our new teammates will be fully integrated with our U.S. teams, working on global projects and gaining exposure to top industry leaders. With continued growth, we will establish a physical office in Bengaluru, India, giving teammates aspace for collaboration and fostering connection.

Now is the perfect time to join Kobie. Be part of something big and help shape the future of our global capabilities center, the Kobie India Tech Hub.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.