Principal Engineer, Team Lead- Data Platform
MotionalSalary not specified
Full Time
Senior (5 to 8 years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
AI, TechnologyIndustries
Requirements
- 9+ years of work experience in software/data engineering (former strongly preferred) as a bachelor's degree holder; 7+ years for master's degree holders; 5+ years for PhD holders
- Served as a tech lead and mentored several data engineers
- Experience in architecting, implementing, and maintaining robust data platform solutions for external-facing data products
- Experience with implementing and maintaining large-scale data processing tools like Beam and Spark
- Experience working with stakeholders and peers from different time zones and roles (e.g., ENG, PM, data science, GTM), often as the main data engineering point of contact
Responsibilities
- Partner with backend and data science to maintain and improve the data platform behind customer-facing analytics operations, including reflecting usage on new features, changes on underlying product usage logs for existing features, identifying and closing data quality issues (e.g., gaps with internal tracking, backfilling changes), triaging customer-reported issues within SLAs, and helping close customer-facing technical documentation gaps
- Help improve the availability of high-value upstream raw data by channeling inputs from data science and business intelligence to identify biggest gaps in data foundations
- Partner with Go-to-Market & Finance operations groups to create streamlined data management processes in enterprise apps like Salesforce, Marketo, and various accounting software
- Partner with Product Engineering teams as they craft product logging initiatives & processes
- Architect and implement key tables that transform structured and unstructured data into usable models for data, operations, and engineering orgs
- Ensure and maintain the quality and availability of internally used tables within reasonable SLAs
- Own and improve the reliability, efficiency, and scalability of ETL tooling (including but not limited to dbt, BigQuery, Sigma), including identifying, implementing, and disseminating best practices
Skills
Key technologies and capabilities for this role
Questions & Answers
Common questions about this position
What is the salary for this Senior Data Engineer position?
This information is not specified in the job description.
Is this role remote or office-based?
The data engineering group is based in the Bangalore, India office.
What are the key responsibilities for this role?
Responsibilities include partnering with backend and data science to maintain and improve the data platform, architecting key tables from structured and unstructured data, improving upstream raw data availability, and ensuring data quality for customer-facing and internal analytics.
What is the team structure like at Glean?
Glean is building a world-class Data Organization composed of data science, applied science, data engineering, and business intelligence groups, with the data engineering group based in Bangalore.
What kind of experience makes a strong candidate for this role?
Strong candidates will have experience partnering with data science, backend, product engineering, go-to-market, and finance teams to build data platforms, handle data quality issues, architect data models, and support customer-facing analytics.
Glean
AI-powered search tool for workplace productivity
About Glean
Glean enhances workplace productivity by providing an AI-powered search tool that works across all applications within a company. This tool utilizes deep learning-based Language Models to understand natural language queries, allowing users to find information more easily. It continuously learns from the specific language and context of a company, improving the relevance of search results without manual adjustments. Additionally, Glean offers a chat assistant that can analyze and summarize information from various company documents and conversations, further increasing efficiency. Unlike many competitors, Glean's focus on natural language processing and its ability to adapt to a company's unique context set it apart. The goal of Glean is to streamline information retrieval in the workplace, making it accessible and efficient for all types of organizations, from startups to large enterprises.
Palo Alto, CaliforniaHeadquarters
2019Year Founded
$637.1MTotal Funding
SERIES_ECompany Stage
Enterprise Software, AI & Machine LearningIndustries
501-1,000Employees
Benefits
Healthcare - Happy and healthy go together. We cover medical, dental, and vision for you and yours.
Competitive compensation - Have a real stake in your job and your future with competitive stock options.
401(k) - We make it easy to save for the future today by contributing to a 401k.
Flexible work - We work 3 days a week in the office, though we believe in folks working where they can be most effective.
Company events - We work hard and play hard - from weekly happy hours to our annual company retreat.
Unlimited PTO - Flexible hours, PTO, company-wide summer and winter break shutdown
Transparent culture - By default we keep things open and accessible so we can make better decisions together, faster.
Learning and development - We offer a learning stipend to help you grow and achieve your goals.
Free meals - With lunch and dinner options every day, no need to work while you’re hungry.
Risks
Inflated valuations in AI could lead to financial instability for Glean.
Competition from tech giants like Microsoft and Amazon pressures Glean's market share.
Opening a new office in Bengaluru may strain resources and impact operational efficiency.
Differentiation
Glean uses AI to enhance workplace productivity with a unique search tool.
The platform integrates with enterprise data, providing personalized, context-aware search results.
Glean's AI assistant offers analyses and summaries, reducing time spent on information retrieval.
Upsides
Glean's $260M funding round doubled its valuation to $4.6 billion in 2023.
The rise of hybrid work models increases demand for Glean's seamless information retrieval tools.
Growing data privacy emphasis allows Glean to offer robust, compliant data hosting options.
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