À propos de ce poste Manager, Field Engineering chez Databricks
FEQ327R115
As a Manager, Field Engineering (Data & AI), you will lead a team of Solutions Architects focusing on large & strategic customers in India. You will help lead our team in India expansion, you will build and lead a technical pre-sales team. You will guide and get involved to enhance your team's effectiveness; be an expert at positioning and articulating business-value-focused solutions to our customers and prospects; whilst coaching new sales and pre-sales team members to work together, support various stages of the sales cycles; and build relationships with key stakeholders in large corporations.
The impact you will have:
- Manage hiring, building the Pre-Sales team consisting of Solutions Architects in the Data & AI domain.
- Rapidly scale the designated Field Engineering segment organisation without sacrificing calibre.
- Build a collaborative culture within a rapid-growth team. To embody and promote Databricks' customer-obsessed, teamwork and diverse culture.
- Support increasing Return on Investment of SA involvement in sales cycles by 2-3x over 18 months.
- Promote a solution and value-based selling field-engineering organisation.
- Coach and mentor the Solutions Architect team to understand our customers’ business needs and identify revenue potential in their accounts.
- Interface with leadership & C-suite stakeholders at strategic customers in the assigned region to position the strength of Databricks, the comprehensive solutions strategy, and build trust and credibility in the account.
- Build Databricks' brand in India in partnership with the Marketing and Sales team
- Bring the experience, priorities, and takeaways of the field engineering team to the planning and strategy roadmap of the organisation.
What we look for:
- 6+ years experience in a pre-sales / consulting / customer facing managerial role: developing, managing and building a team of successful Big Data, Cloud, or SaaS professionals
- Experience working with strategic Banking / Financial Services / Digital Enterprise accounts generating +$1M ARR
- 6+ years experience in Big Data Architecture incorporating components of Data Engineering / Data Warehouse / Machine Learning / Data Science
- Experience in scaling and mentoring field and technical teams managing both in-person and remote working models
- Knowledgeable in and passionate about data-driven decisions, AI, and Cloud software models
- Knowledgeable in Apache Spark™ / Databricks ecosystem
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
