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Lead the Data Revolution at Modus Create. At Modus Create, we empower the world’s most ambitious companies through thoughtful, modern, data-driven digital solutions. As Senior Director of Data Engineering & Machine Learning, you’ll help shape the future by leading inclusive, collaborative teams that architect and scale data platforms, and deliver intelligent AI/ML-powered products. Our work drives transformative outcomes across healthcare, finance, life sciences, automotive, and beyond. We’re seeking a strategic, hands-on leader with a passion for mentoring others, who bridges deep technical expertise with business-driven vision—someone who can shape data and ML strategy, guide clients through transformation, and empower a new generation of data leaders.
Job Responsibility:
Build Modern Data Platforms
Design and oversee architecture for cloud-native data platforms, pipelines, and streaming systems on AWS, Azure, or GCP
Ensure robust solutions using platforms such as Databricks, Snowflake, Redshift, BigQuery, Spark, Kafka, Airflow, dbt, and Kubernetes
Deliver Products that are Intelligent
Define and drive responsible ML strategy, from model development to integration, using platforms like SageMaker, Azure ML, or TensorFlow
Enable smarter client experiences by embedding ML into applications, automation, and analytics
Lead & Grow Teams
Foster a culture of trust, continuous learning, and experimentation by hiring, mentoring, and empowering distributed teams of data and ML engineers
Define career paths, feedback frameworks, and learning programs grounded in a culture of experimentation,continuous growth, and a sense of belonging at every level
Shape Technical Strategy & Best Practices
Develop modular runbooks, tooling standards, and engineering frameworks optimizing for scalability, observability, and security
Champion collaborative practices like Agile/Lean development, dataOps, MLOps, and CI/CD for data pipelines and models
Business Development & Sales Enablement
Partner with Sales, Partnerships, and Account Teams to find and co-create thoughtful, outcome-driven data & ML engagements
Translate client needs into solution designs, shareable collateral, and winning proposals and estimates that reflect both technical strength and business empathy
Serve as a technical leader in pitches, RFPs, and client workshops, establishing Modus as a trusted data, AI, and ML advisor, while building client confidence through clarity and consultative engagement
Cross-Functional Collaboration
Work with product, design, platform, and engineering teams on integrated, end-to-end data solutions
Translate capabilities into human impact by aligning closely with both client technical and business stakeholders
Requirements:
15+ years in data or software engineering roles
7+ years leading Data Engineering/ML teams—ideally at scale or in global consulting contexts
Hands-on experience with cloud data platforms, big data toolchains (Spark, Kafka), data transformation tools (Airflow, dbt), and ML platforms
Success in pre-sales, solutioning, and growing data/ML engagements within enterprise or mid-market accounts
Demonstrated ability to create enablement programs, uplift team capabilities, and grow inclusive, high-performing engineering cultures
Deep empathy for client pain points and the ability to craft and deliver impactful, measurable solutions
Excellent across technical, executive, and cross-functional settings, with an ability to successfully navigate diverse cultural differences
What we offer:
Remote work with flexible working hours
Modus Global Office Programme:for when you want to get out of your home, we offer on-demand access to private offices, meeting rooms, coworking spaces and business lounges in locations in over 120 countries
Employee Referral Program
Client Referral Program
Travel according to client or team needs
The chance to work side-by-side with thought leaders in emerging tech
Access to more than 12,000 courses with a licensed Coursera account
Possibility to obtain paid certification/courses if they align with company goals and are relevant to the employee's role
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