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Company description

Tremend is the newest global software engineering hub for Publicis Sapient. For over 20 years, the company has been infusing its advanced technical expertise into complex and innovative solutions that meet today's digital transformation needs and pave the way for a better and smarter future. By joining forces with Publicis Sapient we're accelerating the impact, providing a good mix of talented engineers, technology, continuous improvement, innovation, and R&D. Here, you'll have the opportunity to unleash your potential, powering up advanced software solutions for some of the world's most iconic brands. Embrace your passion for technology, creativity, and continuous improvement, and join us in making a difference through engineering.

Overview

Tremend is looking for a seasoned Senior Data Engineer to join our growing Data Engineering practice at Tremend. In this role, you will design and deliver enterprise-grade cloud data solutions across modern cloud platforms, while providing technical leadership to a team of engineers working on complex migration and greenfield initiatives.

You will be a key technical voice in client engagements, shaping data platform strategies, driving engineering best practices, and bridging the gap between data infrastructure and AI/ML capabilities. If you thrive at the intersection of robust data engineering, cloud architecture, and applied intelligence, this is your role.

Responsibilities:

• Lead the design and delivery of enterprise cloud data platforms, with hands-on experience on at least one major cloud provider (Azure, GCP, or AWS)

• Architect and optimize large-scale data pipelines and lakehouse solutions using Databricks, Fabric, Apache Spark

• Provide technical leadership and mentoring to a team of mid-level and junior data engineers — conducting code reviews, guiding architecture decisions, and ensuring engineering quality

• Drive end-to-end data engineering initiatives: from requirements and design through to deployment, monitoring, and handover

• Define and enforce data engineering standards including naming conventions, CI/CD practices, data quality frameworks, and documentation

• Collaborate closely with data architects, ML engineers, and business stakeholders to translate complex requirements into scalable, maintainable solutions

• Design and implement medallion architecture (Bronze / Silver / Gold) and Data Vault 2.0 patterns on cloud platforms

• Support AI/ML integration patterns — building feature pipelines, inference data flows, and MLOps-adjacent infrastructure

• Contribute to pre-sales and client scoping conversations, producing technical proposals and effort estimates for data platform engagements

Qualifications:

• 7+ years of hands-on data engineering experience, including at least 2 years in a tech lead or senior individual contributor role

• Databricks knowledge about Delta Lake, Unity Catalog, Spark optimization, and cluster management

• Strong cloud experience, ideally on GCP; extensive experience with Azure or AWS is also highly valued due to platform similarities

• Advanced SQL and PySpark skills; ability to design performant transformations at scale

• Experience implementing medallion architecture and/or Data Vault 2.0 methodologies in a cloud context

• Solid understanding of data pipeline patterns: batch, micro-batch, and streaming (Kafka, Spark Structured Streaming,Pub-sub or equivalent)

• Experience with CDC (Change Data Capture) patterns and tools

• Experience using Terraform and deploying solutions to the cloud using Infrastructure as Code (IaC) practices

• Proven hands-on experience with Snowflake and big data platforms in general

• Strong communication skills — comfortable presenting architecture decisions to both technical teams and business stakeholders

• Proven track record of mentoring engineers and contributing to team capability growth

Nice to Have:

• Hands-on experience integrating data pipelines with AI/ML workloads — feature engineering, model serving data flows, or MLOps pipelines (MLflow, Vertex AI, Azure ML, or equivalent)

• Exposure to LLM-based applications and the data infrastructure they require (vector stores, RAG pipelines, embedding pipelines)

• Experience with legacy-to-cloud migration projects (IBM DataStage, Informatica, SSIS, Talend → cloud-native platforms)

• Relevant cloud or Databricks certifications (Databricks Certified Data Engineer Professional, AWS/GCP/Azure Data certifications)

• Knowledge of EU data regulations relevant to data platform design (GDPR, EU AI Act)

• Experience working in financial services, retail, or other regulated industries

Additional information

Besides an exciting job in a tremendous team, here's what you can expect:

• A fast-paced tech environment

• Continuous growth & learning

• Open feedback culture

• Room for own initiative & ideas

• Transparency about results & strategy

• Recognition & reward for hard work

• Working with a flexible schedule

• Medical subscription

• Meal tickets

• Extra vacation days - starting with 25 vacation days

• Many others perks