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.

Role Description Our Client is hiring a Full‑Stack Data Engineer to strengthen their data foundation and support growing reporting needs across the organization. This is a hands‑on technical role for someone who thrives across the entire data lifecycle from building pipelines and transformations to delivering user‑facing dashboards and predictive insights. You will join a collaborative data team, working closely with engineering and analytics colleagues to ensure reliable data ingestion, efficient workflows, and clear reporting outputs that empower operational and clinical leadership. Key Responsibilities - Data Engineering - Design, build, and maintain data pipelines using GCP tools (BigQuery, Cloud Functions, Cloud Composer, Cloud Scheduler, Apache Beam, Airflow). - Clean, transform, and organize data from multiple sources. - Automate ETL/ELT workflows for reliability and scalability. - Support ingestion from APIs, spreadsheets, and internal systems. - Backend Development - Write Python and Bash scripts to process and automate data tasks. - Develop lightweight backend services and utilities to streamline internal processes. - Front‑End / Dashboards - Build and update dashboards in Looker Studio and D3.js. - Deliver clean, intuitive KPI reports for operations and leadership. - Support visualization needs across the Wellness Division. - Foundational ML / Predictive Work - Contribute to simple predictive modeling and forecasting tasks. - Prepare structured datasets for future machine learning initiatives. Qualifications - Must‑Have: - 2+ years in data engineering, data science, or software engineering. - Strong experience with GCP, including: - BigQuery - Cloud Functions / Cloud Run - Apache Beam & Airflow - Looker / Looker Studio Pro - Vertex AI (AutoML, LLM engineering) - Advanced Python (data processing, APIs, automation). - Experience building end‑to‑end pipelines (batch + streaming preferred). - Strong SQL skills for transformations and modeling. - Proven ability to develop dashboards, KPIs, and BI outputs. - Solid understanding of modern data architectures (lakehouse, warehousing, governance). - Nice‑to‑Have: - Exposure to healthcare or multi‑location environments. - Experience with EMR systems or similar platforms. - Familiarity with predictive analytics and ML workflows. Requirements - Location: South Africa (Remote) - Salary: $1500-$1800 - Time Zone: US Time Zone

Role Description As a Senior Data Engineer, you will drive the end-to-end development of our core data infrastructure through AI-native engineering. Championing our AI DevEx approach, you will orchestrate AI agents to rapidly build, scale, and refactor high-performance systems. We are looking for a technical expert who takes hands-on ownership of distributed, real-time architectures. Leveraging your deep data engineering expertise, you will construct the robust pipelines that power our next-generation data products. - Developing and driving the architecture of complex data systems that prioritize scalability, reliability, and long-term maintainability. - Designing and optimizing production-grade data pipelines, with a primary focus on high-throughput, real-time streaming. - Driving Spec-Driven Development (SDD) using OpenSpec or GitHub Spec Kit to create strict engineering contracts that ensure predictable, high-quality AI code generation. - Orchestrating agentic AI workflows with Claude Code and the Model Context Protocol (MCP) to rapidly build, refactor, and scale our data infrastructure. - Taking full accountability and ownership of system components, working in a self-sufficient manner to solve deep technical challenges. - Implementing rigorous testing and monitoring frameworks to ensure the integrity of mission-critical data. - Mentoring junior engineers and fostering a culture of technical excellence through open feedback and architectural reviews. Qualifications - 10+ years of professional experience, with 5+ years specifically focused on Data Engineering. - Deep technical expertise with Kafka (including Producers, Consumers, and Stream Processing) for building scalable, real-time architectures. - Strong experience with OLAP databases (expertise in Clickhouse is highly preferred). - Good fluency in Python and SQL for complex data manipulation, optimization, and system building. - Willingness to embrace highly agentic AI-assisted development, specifically using Claude Code to autonomously navigate codebases, execute multi-step engineering tasks, and accelerate development cycles while maintaining high code quality. - Strong hands-on experience with Docker, Kubernetes, and automated CI/CD pipelines. - Significant experience with open-source tools and technologies within the modern data stack. - Excellent communication skills and a desire to work in an environment based on transparency and feedback. - Fluency in English. Benefits - Global & Diverse Team: Work in a collaborative, multicultural environment. - Flexibility: Flexible working hours to help you shape your own work-life balance. - Remote-First: A truly remote-friendly environment. - Growth: Ongoing career development, training, and coaching. - Learning Time: Six dedicated days per year for learning and development. - Culture: Regular team events (in-person and virtual) and location-based social benefits.

Role Description As a JUMO Junior Data Engineer, you will design, build and maintain scalable data architectures. You will monitor their performance, perform root cause analysis and provide solutions to any issues that might arise. You will work with large, complex data sets, which means experience working with Big Data is essential. On a typical day, we use Spark, Kafka, Python, SQL, Airflow and AWS technologies, such as Redshift. We work with Docker and Kubernetes for automating deployment, scaling, and management of containerized applications. - Be responsible for creating robust, mission critical batch and streaming data processing capabilities. - Design, implement, and maintain the data pipelines that constitute JUMO's data platform, enabling effective use of data across the organisation. - Provide feedback on team members' output, encouraging skills development within the team. - Work closely with Portfolio Managers and Decision Scientists to understand the real world problems we’re trying to solve. - Be supported by senior leaders as you drive your own development. Qualifications - BSc. in Computer Science, Electrical Engineering or equivalent tertiary degree. - Real-world understanding & experience of data pipeline design and development, as well as data processing and storage. - Experience in streaming technologies, specifically Spark and Kafka. - Experience with cloud technologies, AWS preferred. - Solid, proven experience working with big-data technologies such as Apache Spark, Flink, Hadoop, Kafka or Kinesis, DynamoDB. - Command of productionising and monitoring of data pipeline workflows, and working knowledge of the Data Product Lifecycle. - Experience in application design and development with at least one of the following languages: Python (preferred), Kotlin. - RDBMS experience in any relevant technology such as MySQL, PostgreSQL, Redshift and SQL Server. - Understanding of CI/CD practices. - Productive within a Linux command line environment. - Proven ability to contribute software as part of a team. Requirements - Experience working with messaging systems (RabbitMQ, Redis, SNS) - Bonus. - Experience working with data pipeline orchestration (Airflow, Nifi, Dagster) - Bonus. - Experience working with production BI environments and tools (Tableau, Superset, Looker) - Bonus. Benefits - Collaborating with smart, engaging people in an inspiring work environment. - Working for impact. - Growing and learning continuously, with loads of encouragement and support. - Boldly taking risks as we navigate new challenges. - Flexible work practices enabling your best delivery. - Being autonomous and empowered to lead. - A stack of leading-edge technologies. Company Description At JUMO, we’ve built a smart financial services platform to make finance accessible to everyone. We operate a remote first working approach, where working remotely is our default way of working. Our environment is designed to foster innovation and enable collaboration. - Diversity strengthens our teams. - We are dedicated to fostering an inclusive recruitment process that cultivates an environment where all individuals can be authentic, collaborate, and thrive.