Data Technical Lead

Key Responsibilities

Technical Leadership & Strategy

• Define and evolve the data architecture and cloud infrastructure to support enterprise analytics, AI, and
  - driven
  - making, and being responsible for having the data landscape architecture stable
• Translate business requirements into scalable, secure, and
  - performance data solutions.
• Evaluate emerging technologies, tools, and frameworks to improve platform performance and maintainability.
• Understand all our current data architecture.
• Plan and support the conception of
  -
  - end data models for new data solutions and its consumption.
• Propose new data architectures, prepare migration plans & data ETL models.
• Support the Data Manager over data quality and data concepts.

Solution Architecture

• Design
  -
  - end data solutions across ingestion, storage, processing, and consumption layers.
• Ensure architectural standards, guidelines, and best practices are followed.
• Lead cloud infrastructure design and optimization (Azure, Databricks, AWS, GCP).
• Implement and support Data security, Understanding of GDPR concepts and its consequences for stored data.
• Research and discover the most efficient methods to acquire data, monitor database performance and suggest needed changes, apply security best practices to data, document and update all the data solutions.

Team Leadership & Collaboration

• Mentor and guide data engineers and cloud specialists, promoting technical excellence.
• Work closely with data governance, analytics, and product teams to align on priorities.
• Foster a culture of innovation, quality, and accountability.
• Support technically and functionally DBA’s and Data Delivery teams.

Delivery & Operations

• Oversee the delivery of
  - quality,
  - grade data pipelines and services.
• Ensure systems meet SLAs, compliance, and security requirements.
• Troubleshoot complex technical issues across the data stack.
• Present different (unbiased) technological solutions with pros & cons, cost & resource estimations.

Required Skills & Experience

Technical Skills

• Proven experience in data engineering and data architecture (5+ years).
• Strong proficiency in cloud platforms (Azure, Databricks, AWS, or GCP) and
  - native data services.
• Expertise in data modeling, ETL/ELT, streaming, and data lake/data warehouse architectures.
• Experience in solution designs, data flows and data analysis.
• Good understanding and experience with ML, Reporting, Dashboards, Big Data, Data Consumption, ETL processes, Data Migrations, and AI.
• Experience in writing guidelines and architectural / technical / functional documentation.
• Strong programming skills in Python, SQL, and one other modern language (e. g. , Scala, Java, R, Spark, etc. ).
• Experience with
  -
  - code tools (Terraform, ARM/Bicep, Cloud
  Formation).
• Solid understanding of Dev
  Ops and CI/CD for data solutions.