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We are looking for a Tech Lead - Data Platform.
As a tech lead, you will take a leading part in designing and building the infrastructure for connecting and analyzing huge, privacy protected datasets in the cloud using Java, Spark and other technologies and mentor team members.
What You'll Do:
Design and develop platform capabilities for scalable data products tailored to enterprise customers
Collaborate with Product Managers, Software Engineers, and DevOps Engineers to gather requirements, create system and feature design documentation, and implement solutions across diverse environments
Write Java-based back-end code, leveraging Spark, various cloud services, and relational databases
Partner with the production team to define solutions, monitor services, troubleshoot issues, and identify cost optimization opportunities
Mentor and guide team engineers, providing support in their daily tasks and development
Build and use monitoring infrastructure to track services, troubleshoot problems, and optimize performance, throughput, and costs
Address privacy challenges to ensure the protection and confidentiality of consumer and patient data

We are looking for a Analysis Team Lead to join our team!
As an Analysis TL, you will lead a team of CS analysts and product analysts. The team is in charge of analyzing our products existing and newly released features, works closely with our product squads and takes part in the product design, implementation and testing. In addition, the team supports the CS departments business operations. It plays a major role in understanding and nurturing our growing customer base, by exploring the adoption of our product by our users, building usage metrics, and exploring ways to increase customer engagement and prevent churn. As a TL, you will be the professional guide for the team, manage their tasks and priorities, and take part in the more complex analytic projects. You will share the team reports and business insights with key business stakeholders in the company, and become the trusted data advisor of the Product and CS departments.
Responsibilities
Lead a multidisciplinary team of exceptionally talented analysts.
Lead the design and implementation of data models, prediction models, and KPIs working closely with the BI dev team.
Oversee the building and maintenance of reports, dashboards, and metrics
Drive data research and exploration to deliver actionable insights that support business performance.
Identify areas for improvement and make recommendations for new opportunities for growth
Develop strong partnerships with product and CS leaders to achieve business objectives and become their trusted data advisor.

The Senior system architect will lead a team responsible for the design and maintenance of data architecture and systems in the cloud, with a focus on Google Cloud.
The candidate will be responsible for developing POCs, writing system and data architecture documentation, performing cloud migration processes, and building Machine Learning models in Python.
The role also requires team leadership skills and the ability to manage and deliver tasks with high performance.

We are looking for a Data Engineering Team Lead to drive the development and optimization of our data infrastructure.

So, what will you be doing all day?

Lead & Mentor: Provide technical leadership and mentorship, setting clear goals, fostering innovation, managing stakeholders and guiding the professional growth of the team.
Data Infrastructure Development: Design and enhance scalable data architectures and pipelines to support current and future business needs.
ETL & Data Processing: Develop and maintain ETL processes, integrating data from various sources (APIs, databases, external platforms) using Python, SQL, and cloud technologies.
Cloud & Big Data Technologies: Implement solutions using PySpark, Databricks, Airflow, and cloud platforms (AWS) to process large-scale datasets efficiently.
Monitoring & Optimization: Ensure system reliability, observability, and performance using monitoring, logging, and alerting tools.
Collaboration & Stakeholder Engagement: Work closely with BI analysts, business stakeholders, and cross-functional teams to define data requirements and enable self-service BI capabilities.
Data Modeling: Design and maintain logical and physical data models to support analytics and operational needs.