Senior Data Analytics Developer for Krux, building data infrastructure for innovative SaaS solutions in mining industry. Collaborating with a self - motivated team to drive company growth.
About the role
- Analytics Engineer building and maintaining data infrastructure for PermitFlow's AI platform. Collaborating with teams to optimize analytics processes and ensure data integrity while supporting decision-making.
Responsibilities
- Design and implement scalable data models optimized for analytics and company-wide reporting, continuously refining them to meet evolving business needs.
- Build and maintain efficient data pipelines to transform datasets for analytics.
- Collaborate with product and engineering teams to integrate data from sources like PermitFlow’s CRM, 3rd party vendors, and other internal sources while optimizing for performance and reliability.
- Implement data governance to ensure consistency, quality, and security. Define key metrics, track data lineage, and enforce data quality checks.
- Work closely with stakeholders to deliver analytics solutions, develop dashboards, and provide training on data tools and best practices.
- Manage and optimize PermitFlow’s data stack to support scalable reporting and insights.
Requirements
- 3+ years of experience in analytics engineering, data engineering, or data analytics roles.
- Strong proficiency in PostgreSQL, SQL, dbt, or similar data warehousing technologies.
- Experience with ETL pipelines and tools, or other modern data stack tools.
- Advanced programming skills in Python or other languages for data transformation and analysis.
- Proven experience designing data models and building scalable data warehouses for analytics purposes.
- A deep understanding of data governance, data quality practices, and developing self-serve analytics solutions.
- Strong communication and collaboration skills, with the ability to explain technical concepts to non-technical stakeholders.
- Experience with business intelligence tools like Looker, Tableau, or Power BI, and familiarity with cloud platforms like Google Cloud.
Benefits
- Competitive salary and meaningful equity in a high-growth company
- Comprehensive medical, dental, and vision coverage
- Flexible PTO and paid family leave
- Home office & equipment stipend
- Hybrid NYC office culture (3 days in-office/week) with direct access to leadership
- In-Office Lunch & Dinner Provided
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Lead Risk Analytics Consultant at Wells Fargo focused on model governance and risk management strategies. Collaborate across teams to enhance system stability and mentor junior staff.
Analytics Engineering Lead responsible for building data products at Sanlam Fintech. Overseeing analytics engineering practice modernization and talent development within the organization.
Analytics Engineer foundational technical pillar for Analytics & Data Engineering at Skin + Me, transforming raw data into a strategic engine for growth. Reporting to the Director of Data and optimizing performance across business units.
Senior Analytics Engineer at RB Global designing domain models and leading KPI efforts. Optimizing data performance and mentoring analytics engineers in a hybrid work environment.
Analytics Engineer transforming raw data into analytics - ready datasets for dashboards and data products. Building data models in Snowflake and developing LookML for analytics at RB Global.
Analytics Engineer transforming data into actionable insights at Zopa. Collaborating with teams to build high - quality data products and support business growth.
Senior Analytics Engineer at Bauer Media Outdoor transforming data into trusted datasets for decision making. Design and maintain data models, ensuring analytical usability and quality across the business.
Analytics Engineer building data pipelines and metrics at Sibill. Developing actionable insights from business - critical data while collaborating across teams in a hybrid model.
Jr Analytics Engineer at Klar designing and maintaining data infrastructure for financial services. Focused on ensuring data quality and providing actionable insights for business decisions.