Job Description

We re MiQ, a global programmatic media partner for marketers and agencies. Our people are at the heart of everything we do, so you will be too. No matter the role or the location, we re all united in the vision to lead the programmatic industry and make it better. As a Tech Lead in our Technology department, you require Strong experience in Big Data technologies Proven expertise in building and managing data platforms, with a focus on data modelling, pipeline orchestration, and data processing. Solid understanding of microservice architecture , including designing and integrating microservices for data platform interoperability. Experience in Ops frameworks - implementing and managing scalable and reliable ML/data pipelines in production environments. Deep knowledge of access management and data security , including user role provisioning, auditing, and compliance. Proficient in infrastructure management - cloud platforms (AWS preferred), networking fundamentals , VPC, routing, subnets, and firewalls. Experience with cost governance and optimisation across data and compute workloads (e.g., using Databricks cost controls, AWS cost explorer). Familiarity with deployment strategies , CI/CD pipelines, and infrastructure-as-code (Terraform, CloudFormation, etc.). Strong background in Python, PySpark , and at least one JVM-based language (Java/Scala/Kotlin) for data application development. Solid grasp of DevOps principles with working knowledge of release management, automation, and monitoring tools (e.g., Jenkins, Prometheus, Graphana). Familiarity with data governance , cataloging, and metadata management tools (e.g., Unity Catalog, Amundsen, Apache Atlas). Experience leading cross-functional data initiatives , coordinating between data engineers, ML engineers, Data Scientists, and Business Analysts. Strong problem-solving mindset with a passion for R&D in data technologies and innovation . Who are your stakeholders 1. Business Analyst Data Engineers Data Scientist What you ll bring Technical Expertise : Deep understanding of the latest Big Data technologies (Spark Engines, Sql Engines like Databricks, Apache pinot, EMR, etc) and proficiency in building and managing complex data pipelines . Strategic Vision : Ability to define and execute the long-term vision for data platforms, ensuring alignment with business objectives and evolving technological trends. Leadership in DataOps & MLOps : Driving operational efficiency and reliability in data pipelines and ML workflows. Platform Optimisation : Experience in optimising platform performance and cost management , ensuring scalable solutions that meet organisational needs without exceeding budget. Innovation and R&D : A forward-thinking mindset with a passion for exploring new data technologies , continuously seeking ways to enhance platform capabilities and efficiency. Infrastructure Management : Proven experience managing cloud-based infrastructures , including networking, deployment, and monitoring , while ensuring reliability and high availability. Governance and Metadata Management : Knowledge of data governance frameworks , ensuring proper data cataloging, lineage, and metadata management to drive data quality and transparency. Proactive Problem Solver : Strong analytical skills, with a solution-oriented approach to overcoming technical challenges and finding innovative solutions for complex data problems. Cost Efficiency : Ability to implement cost optimisation strategies and ensure resource utilisation is efficient, helping the team minimise waste and maximise value. Security Best Practices : Implementing best practices in data security , including encryption, hashing, key management, and access controls, to protect sensitive data across platforms.