Senior Data Engineer New Helsinki, Uusimaa, Finland

Smartly; Helsinki; Hybrid; EUR 90,000 - 120,000; Full time

Benefits offered by this job

Inclusive culture

Global impact

Wellbeing support

Equity options

Flexible hybrid workspace

Job summary

Smartly in Helsinki is seeking a Senior Data Engineer to join the Data Platform. You will build and operate pipelines to move data into BigQuery, shape datasets, and optimize performance and cost.

You will work with a cloud-stack including Google Cloud, BigQuery, dbt, and Airflow, delivering dependable datasets across product analytics and business decisions. This role offers flexibility with a hybrid work model and opportunities to impact data reliability and cost.

Qualifications

• Experience building data warehouses from ingestion to publishing data products.
• Strong SQL and Python skills, with a track record of writing clear, maintainable code.
• Solid understanding of data storage and warehouse design, including how structure, volume, access patterns, retention affect reliability, performance, cost and data modelling.
• Experience developing and supporting Airflow workflows or similar orchestration tool.
• Practical dbt experience, including models, tests, documentation, and version-controlled deployment workflows.
• Experience with solving production issues in data warehouse.
• Clear written and spoken English, and the ability to work effectively with engineers and analysts.

Responsibilities

• Build and operate batch and incremental ingestion pipelines in Google Cloud to Smartly Data Platform.
• Develop Airflow workflows using Python with best orchestration practices, including dag dependencies, retries, backfills, alerting, and recovery.
• Build and maintain dbt transformations, from source-aligned staging models to curated warehouse datasets. Add tests and documentation, and support version control and deployment checks.
• Design practical storage patterns across Cloud Storage and BigQuery, considering formats, data grain, partitioning, clustering, retention, lifecycle, and access controls.
• Improve data warehouse performance and cost through ongoing query and storage optimization.
• Document data flows and operational practices so pipelines are understandable, supportable, and safe to extend.
• Work with analytics, product engineering, and platform colleagues to clarify requirements and deliver dependable datasets.
• Monitor freshness, completeness, volume, and schema changes so data problems are visible and addressed early.
• Investigate pipeline failures and data discrepancies from source through downstream models, correct the root cause, and validate recovery.

Skills

SQL

Python

Data modelling

English communication

Tools

BigQuery

Airflow

dbt

Cloud Storage

Google Cloud Platform

Kubernetes

Job description

We are looking for a Senior Data Engineer to join the Data Platform at Smartly!

Smartly is an AI-powered advertising platform uniting creative and media workflows. We help brands create, manage, optimise, and understand digital advertising across major media platforms.

The Data Platform team builds the data foundations that support product development, product analytics, and business decisions. In this role, you will build and operate the pipelines that bring data from Smartly’s product and business systems into BigQuery, then shape it into dependable datasets used across the company.

Our production data stack includes Google Cloud, BigQuery, dbt, Airflow and Python. You will work across ingestion, storage, orchestration, modelling, and operations. Strong judgement about data storage matters: how data is structured, retained, and served affects reliability, usability, performance, and cost.

You will work closely with Product Analytics, BI, product engineering, and data-platform engineers. Together, we make data easier to discover, trust, and use.

What you will do

• Build and operate batch and incremental ingestion pipelines in Google Cloud to Smartly Data Platform.
• Develop Airflow workflows using Python with best orchestration practices, including dag dependencies, retries, backfills, alerting, and recovery.
• Build and maintain dbt transformations, from source-aligned staging models to curated warehouse datasets. Add tests and documentation, and support version control and deployment checks.
• Design practical storage patterns across Cloud Storage and BigQuery, considering formats, data grain, partitioning, clustering, retention, lifecycle, and access controls.
• Improve data warehouse performance and cost through ongoing query and storage optimization.
• Document data flows and operational practices so pipelines are understandable, supportable, and safe to extend.
• Work with analytics, product engineering, and platform colleagues to clarify requirements and deliver dependable datasets.
• Monitor freshness, completeness, volume, and schema changes so data problems are visible and addressed early.
• Investigate pipeline failures and data discrepancies from source through downstream models, correct the root cause, and validate recovery.

What we are looking for

• Professional experience on building data warehouses starting from data ingestion and landing to publishing data products.
• Strong SQL and Python skills, with a track record of writing clear, maintainable code.
• A solid understanding and hands on experience on data storage and warehouse design, including how structure, volume, access patterns, and retention affect reliability, performance, cost and data modelling.
• Experience developing and supporting Airflow workflows or similar orchestration tool
• Practical dbt experience, including models, tests, documentation, and version-controlled deployment workflows.
• Experience with solving production issues in data warehouse.
• Clear written and spoken English, and the ability to work effectively with engineers and analysts.

Useful experience, but not required

• Google cloud development stack: Google Cloud Storage, BigQuery, Cloud SQL, PostgreSQL, or other Google Cloud data services.
• Kafka or other event-streaming systems, and familiarity with Kubernetes.
• Data lineage, cataloguing, observability, Tableau, or Redash.
• Advertising, marketing, or product analytics data.

What we offer you

At Smartly, we offer a place where you can do meaningful technical work while growing with a global team.

• Inclusive global culture built on trust, transparency, open feedback, and respect for different perspectives.
• Global impact through technology used by major brands to plan, create, optimize, and understand digital advertising at scale.
• Wellbeing support, paid holidays, family leave, and sustainable ways of working.
• Equity options, performance-based rewards, competitive compensation, and career development opportunities.
• A flexible hybrid workplace that balances office collaboration with focused remote work.

About Smartly

Smartly is the AI-powered advertising technology company transforming ad experiences for brands and their consumers. Our comprehensive advertising platform seamlessly integrates the capabilities of media, creative, and intelligence to power more than 800 billion impressions and generate more than 300 billion creatives annually, delivering tangible business outcomes for brands and advertisers.

Smartly is the only company in the industry recognized as a Leader in The Forrester Wave: Creative Advertising Technologies with PwC validating the results it delivers for brands. We manage creative and media for 700+ brands worldwide and $6B in ad spend across the largest media platforms, including Facebook, Google, Instagram, Pinterest, Snap, and TikTok. Our end-to-end technology, unmatched access to media platforms and exceptional customer service help Fortune 500 brands to reach and engage consumers and learn what performs best.Smartly is a multinational and diverse team of 750+ Smartlies from 60+ nationalities, working in 13 countries. Together, we want to create and maintain an inclusive environment where everyone feels respected and heard. Our Diversity, Equity & Inclusion approach is at the heart of it.