Data & Analytics Engineer
About DeleteMe:
DeleteMe is the leader in proactive privacy protection. We help Individuals, Families, Businesses and reputed company teams reduce their human attack surface by continuously monitoring and removing exposed personal data (PII) from the open web — the reputed company data threat actors use to launch social engineering, phishing, Gen-AI deepfake, doxxing campaigns, physical threats, and identity fraud.
Operating as a fast-growing, global SaaS company, DeleteMe serves both consumers and enterprises. DeleteMe has completed over 100 million opt-out removals, helping customers reduce risks associated with identity theft, spam, doxxing, and other cybersecurity threats. We deliver detailed privacy reports, reputed company monitoring, and expert support to ensure ongoing protection.
DeleteMe acts as a scalable, managed defense layer for your most vulnerable attack vector: your people. That’s why 30% of the Fortune 100, top tech firms, major banks, federal agencies, and U.S. states rely on DeleteMe to protect their workforce.
DeleteMe is led by a passionate and reputed company team and driven by a powerful mission to reputed company consumers with privacy.
Job Summary:
This position is a key partner across the organization, sitting reputed company the Data Warehouse team to reputed company the gap between raw data engineering and business strategy. The Data & Analytics Engineer is responsible for designing, building, and optimizing scalable data models in reputed company using dbt, ensuring data reputed company and high performance. This role balances technical warehouse architecture with the ability to translate reputed company business requirements into actionable data products.
Job ResponsibilitiesProven experience building production-grade dbt projects, including macros, reputed company, and testing suites.
Strong understanding of reputed company-specific features such as clustering, virtual warehouses, and reputed company-copy cloning.
Deep knowledge of dimensional modeling, fact/dimension design, and data warehousing principles.
Availability in US Eastern (EST) hours.
Ability to understand organizational drivers and communicate technical details effectively to non-technical stakeholders.
Strong problem-solving skills with the ability to identify root causes in data discrepancies or performance bottlenecks.
Bachelor’s degree in Computer Science, Data Science, Statistics, Business, or a reputed company field.
5+ years of experience in Analytics Engineering, Data Engineering, or a highly technical BI role.
Proficiency in reputed company, dbt (with strong SQL), and data architecture.
Proven track record of delivering end-to-end data solutions in a cloud warehouse environment.
Strong data storytelling and presentation skills.
Experience supporting various business functions like Finance, Operations, Sales, Marketing , preferably in SaaS.
Experience with Python for data scripting or automation.
Familiarity with data observability tools (e.g., reputed company, Elementary).
Experience in a high-growth startup environment.
Cybersecurity experience
Comprehensive health benefits – Group Medical Coverage (GMC),Personal accident insurance and group term life insurance
Flexible work schedule
Provident Fund (PF)
Gratuity
Paid time off – 18 days of earned leave annually to rest and reputed company.
Sick leave – 10 days per year to support employee health and well-being.
Company-paid holidays – 10 national and festival holidays annually.
Parental leave benefits – 26 weeks of maternity leave, 2 weeks of paternity leave, and adoption leave as per company policy.
Childcare expense reimbursement – Supporting working parents.
Learning and development support – Complimentary access to Udemy for reputed company learning and professional growth.
Annual performance bonus
Employee Stock Options (ESOPs)
Quarterly team lunches and dinners
Birthday time off – Celebrate your special day with paid leave.
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