Role overview

Qualifications

6+ years experience in a pre-sales / consulting / customer facing managerial role
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
Knowledgeable in Apache Spark™ / Databricks ecosystem

Responsibilities

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
Coach and mentor the Solutions Architect team to understand our customers’ business needs
Build Databricks' brand in India in partnership with the Marketing and Sales team

Key facts

Remote from: India
Full time
Senior (5-10 years)
Engineering Manager
English

Hard skills

Solution Architecture Big Data Cloudant Machine Learning Data Engineering Data Science Apache Spark Databricks Artificial Intelligence Customer Relationship Management

Other skills

Team Leadership
Coaching
Collaboration

About the company

Databricks

Computer Software / SaaS

Databricks is the data and AI company. More than 7,000 organizations worldwide — including Comcast, Condé Nast, H&M, and over 40% of the Fortune 500 — rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world’s toughest problems.

Company details

Company typeXLarge

IndustryComputer Software / SaaS

Company size5001 - 10000

Links

Website LinkedIn See all jobs

Your match analysis

See how your profile stacks up against this role.

We compared the job requirements to your profile to show where you're strong and where you fall short.

Job description

FEQ327R192

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.

Apply once. Then go straight to the hiring manager.

After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.