• This role focuses on building the data foundations that enable advanced analytics and machine learning at scale. • You will design and develop data pipelines and architectures that support real-time insights and AI-driven applications across the business. • Working with large, complex datasets, you will ensure data is reliable, accessible, and optimized for both analytics and machine learning use cases. • Develop data models and warehouse schemas optimized for analytics and machine learning. • Build and maintain data ingestion frameworks using streaming systems (Kafka, Kinesis) and batch processing (Spark, Airflow). • Build and manage feature stores to support ML model training and inference. • Integrate data from multiple sources into a unified architecture. • Implement data quality validation frameworks and monitoring systems. • Optimize data pipelines for performance, scalability, and cost efficiency.

• Lead the evolution of intelligent platforms across our enterprise customer division. • Champion strategic initiatives leveraging data, analytics, and artificial intelligence to enhance customer experiences. • Shape data architecture, artificial intelligence strategy, and governance models for automation, MLOps, and insights. • Collaborate with business and technology partners for modern, secure, and adaptive data ecosystems and AI solutions. • Contribute to establishing a future-ready data foundation.

• Build and support non-interactive (batch, distributed) & real-time data pipelines • Build fault-tolerant, self-healing, adaptive, and highly accurate data computational pipelines • Provide consultation and lead implementation of complex programs • Develop and maintain documentation for assigned systems and projects • Tune queries over billions of rows of data in a distributed query engine • Perform root cause analysis for software/business process issues • Implement and maintain dbt transformation models, CI pipelines, data contracts • Build and monitor data quality gates and freshness SLOs • Optimize BigQuery cost and performance with query tuning, storage design • Implement platform hardening controls including retries, dead-letter queues

Role Description As a Senior Big Data Engineer, working within Placer.ai's Mobility Group, you will play a pivotal role in designing, developing, and maintaining the data infrastructure that powers our location analytics platform. Responsibilities - Data Pipeline Architecture and Development: Design, build, and optimize robust and scalable data pipelines to process, transform, and integrate large volumes of data from various sources into our analytics platform. - Data Quality Assurance: Implement data validation, cleansing, and enrichment techniques to ensure high-quality and consistent data across the platform. - Performance Optimization: Identify performance bottlenecks and optimize data processing and storage mechanisms to enhance overall system performance and reduce latency. - Cloud Infrastructure: Work extensively with cloud-based technologies (GCP and AWS) to design and manage scalable data infrastructure. - Collaboration: Collaborate with cross-functional teams including Data Analysts, Data Scientists, Product Managers, and Software Engineers to understand requirements and deliver solutions that meet business needs. - Data Governance: Implement and enforce data governance practices, ensuring compliance with relevant regulations and best practices related to data privacy and security. - Monitoring and Maintenance: Monitor the health and performance of data pipelines, troubleshoot issues, and ensure high availability of data infrastructure. - Mentorship: Provide technical guidance and mentorship to junior data engineers, fostering a culture of learning and growth within the team. Qualifications - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. - 5+ years of professional experience in software development, with at least 3 years as a Data Engineer. - Spark expertise (mandatory): Strong proficiency in Apache Spark, including hands-on experience with building data processing applications and pipelines using Spark's core libraries. - PySpark/Scala (Mandatory): Proficiency in either PySpark (Python API for Spark) or Scala for Spark development. - Data Engineering: Proven track record in designing and implementing ETL pipelines, data integration, and data transformation processes. - Cloud Platforms: Hands-on experience with cloud platforms such as AWS, GCP, or Azure. - SQL and Data Modeling: Solid understanding of SQL, relational databases, and data modeling. - Big Data Technologies: Familiarity with big data technologies beyond Spark, such as Hadoop ecosystem components, data serialization formats (Parquet, Delta), and distributed computing concepts. - Programming Languages: Proficiency in programming languages like Python, Java, or Scala. - ETL Tools and Orchestration: Familiarity with ETL tools and frameworks, such as Apache Airflow. - Problem-Solving: Strong analytical and problem-solving skills. - Collaboration and Communication: Effective communication skills and collaboration within cross-functional teams. - Geospatial Domain (Preferred): Prior experience in the geospatial or location analytics domain is a plus. Requirements - 5+ years of professional experience in software development, with at least 3 years as a Data Engineer. - Spark expertise (mandatory): Strong proficiency in Apache Spark. - PySpark/Scala (Mandatory): Proficiency in either PySpark or Scala. - Data Engineering: Proven track record in designing and implementing ETL pipelines. - Cloud Platforms: Hands-on experience with AWS, GCP, or Azure. - SQL and Data Modeling: Solid understanding of SQL and relational databases. - Big Data Technologies: Familiarity with big data technologies beyond Spark. - Programming Languages: Proficiency in Python, Java, or Scala. - ETL Tools and Orchestration: Familiarity with ETL tools and frameworks. - Problem-Solving: Strong analytical and problem-solving skills. - Collaboration and Communication: Effective communication skills. - Geospatial Domain (Preferred): Prior experience in the geospatial domain. Benefits - Join a rocketship! We are pioneers of a new market that we are creating. - Take a central and critical role at Placer.ai. - Work with, and learn from, top-notch talent. - Competitive salary. - Excellent benefits.