Senior Analytics Data Engineer

We are looking for a Senior Data Engineer to join the project team of our Client, a fast-growing company from the Silicon Valley, that develops a mobile app which provides millions of families in over 150 countries with services such as private location sharing, location history, drive details, crash detection, roadside assistance and help alerts through our free and paid membership subscription. Their customer base currently exceeds 66 million monthly active users. The company is at the forefront of a broad range of technologies (mobile, location services, hardware sensors, machine learning, big data, etc) in pioneering its family-centric platform.

Their Analytics Data Engineering team’s purpose is to design, build, and maintain scalable and efficient data infrastructure that empowers teams to make data-driven decisions. We transform raw data into reliable, accessible, and actionable insights, ensuring data quality, compliance, security, costs and performance at every step. By leveraging innovative technologies and best practices, we enable organizations across the business to unlock the full potential of data, driving operational excellence and strategic growth.

Requirements:

• Minimum 5+ years of experience in analytics engineering, data modeling, or similar roles working with enterprise-scale data, and demonstrated ownership of data products and cross-functional collaboration
• Expert-level SQL skills with a deep understanding of query optimization and performance tuning
• Extensive experience with dbt (data build tool), including testing, documentation, and package management
• Strong programming skills in Python for data manipulation, automation, and custom analytics workflows
• Strong understanding of dimensional modeling, star schemas, one big table, and other data modeling methodologies
• Experience with modern cloud data warehouses (Snowflake, BigQuery, Redshift, or Databricks)
• Familiarity with orchestration frameworks (Airflow) and how analytics transformations are scheduled within broader data workflows
• Experience working with version control systems (Git) and implementing CI/CD for analytics code
• Strong business acumen and ability to translate business requirements into
  well-designed data models
• Understanding of data governance, privacy, and compliance requirements (GDPR, CCPA, and SOX)

Responsibilities:

• Design and implement robust dimensional and relational data models that support analytical use cases for organizations across the business
• Build and maintain scalable dbt transformation pipelines, ensuring high data quality, performance, and cost-efficiency from raw ingestion to business-ready outputs
• Own the transformation and modeling of curated (Silver/Gold) datasets, ensuring clear contracts and traceability from raw to business-ready data.
• Collaborate with data analysts, product analytics, data scientists, and business stakeholders to translate requirements into durable data products that support experimentation, A/B testing, and advanced analytics
• Implement data quality tests, monitoring, SLAs, and alerting to ensure reliability of critical analytical datasets
• Partner with Data Engineers to define and enforce data contracts, ensuring schema stability and minimizing downstream breakage
• Follow analytics engineering best practices, including version control, testing standards, and documentation
• Empower self-service analytics by building intuitive, well-documented data marts and semantic layers

We offer:

• Competitive salary
• Vacation (up to 20 working days)
• Paid sick leaves (10 working days)
• Medical reimbursement after 3 months
• National Holidays as paid time off
• Flexible working schedule, remote format
• Direct cooperation with the customer
• Dynamic environment with low level of bureaucracy and great team spirit
• Challenging projects in diverse business domains and a variety of tech stacks
• Communication with Top/Senior level specialists to strengthen your hard skills
• Online teambuildings