Data Engineer II

Distilled; Dublin; Ibrido; EUR 70.000 - 110.000; Tempo pieno

Vantaggi offerti da questo lavoro

Generous leave

Healthcare

Pension contributions

Hybrid work

Commuter scheme

Bike to Work

Development plan

Descrizione del lavoro

Distilled is seeking a Data Engineer II in Ireland to transform data from leading marketplaces into actionable insights. You will build data pipelines, model data, and support predictive features powering Daft.ie, DoneDeal.ie, and Adverts.ie. Collaboration across teams and a growth mindset are valued.

The role offers hybrid work between home and our Dublin city centre office, with strong focus on data quality, scalable architectures, and production ML workflows using AWS tools.

Competenze

• 2+ years proven data engineering experience, with some exposure to machine learning in production.
• Hands‑on experience with SQL (DDL, DML) and Python in your role(s).
• Experience with relational databases (Redshift, Postgres, MySQL).
• Experience on large‑scale data warehousing and analytics projects in distributed systems.
• Exposure to production ML workflows is a plus.

Mansioni

• Developing data pipelines and transformations to support data production and consumption.
• Ensuring data is trusted by consumers and stakeholders for timely insights.
• Driving data modeling to create consumable data sets for end-users.
• Building feature pipelines and training workflows for predictive models.
• Supporting platform maintenance to ensure smooth operations.
• Collaborating with product teams to provide data for features on our sites.
• Working with AI tooling and AWS services to power AI use cases.

Conoscenze

SQL

Python

Data warehousing

AWS

PostgreSQL

ML exposure

Strumenti

Redshift

PostgreSQL

MySQL

S3

Glue

Lambda

Athena

Kinesis

Descrizione del lavoro

What’s the Opportunity

We’re looking for a Data Engineer II to help us turn the vast amounts of data generated by Ireland’s leading online marketplaces - Daft.ie, DoneDeal.ie and Adverts.ie - into useful insight for our users and employees.

In this role, you will build processes to ingest, store and transform the data so that it can be used for reporting and insights, to power features on our websites including predictive models.

How you’ll Create with Impact

• Developing data pipelines and associated data transformations that support data production and consumption throughout the organisation
• Ensuring our data is trusted by our data consumers, colleagues and partners and that we provide timely and appropriate data to support the business
• Driving data modeling activities to simplify raw data into consumable data sets for end-users
• Building and maintaining feature pipelines and training/scoring workflows for predictive models in production
• Supporting the platform maintenance activities to ensure ongoing smooth operation
• Collaborating with Daft and DoneDeal application development teams to provide the data needed for some data features for end users on our websites
• Working with modern AI tooling such as Amazon Bedrock to power AI use cases on Daft and DoneDeal; and internal tooling for data self-serve

What you’ll need to Play your Part

• A collaborative spirit and growth mindset
• At least 2 years proven data engineering experience, with some exposure to machine learning in production
• Hands‑on experience with SQL (DDL, DML) and Python in your role(s). (Most of our production systems are Java based, however the data team uses Python)
• Experience with relational databases (Redshift, Postgres, MySQL).
• Experience working on large-scale data warehousing and analytics projects, built on highly available, distributed systems
• Experience working on large-scale data warehousing and analytics projects

Advantage if you have experience with

• Building or productionising machine learning workflows in Python (e.g. scikit-learn, XGBoost) and a solid grasp of how to evaluate model performance
• Cloud technologies. (We use AWS technologies such as Redshift, Lambda, Athena, S3, Kinesis, Glue, Bedrock and Sagemaker)
• ML platforms and MLOps tooling (e.g. SageMaker, feature stores, model monitoring)

How we help you Thrive Here

We want you to do your best work and we’ll support you to do just that with:

• Generous paid leave: Start with 22 days' annual leave, plus 3 company days over Christmas. Every August we take four Fridays off as "Thank You Days", our way of saying thanks for your hard work. Stay with us and you'll earn an extra day's leave on each of your first four anniversaries, up to 26 days.
• Looking after you: Your Irish Life Healthcare is fully paid for, and we run regular health and wellbeing talks, events and activities all year.
• Investing in your future: We contribute 5% to your pension through our contributory scheme, so you can plan with confidence.
• Work where it works for you: Split your time between home and our Dublin city centre office, a short walk from St Stephen's Green and St Patrick's Cathedral.
• Get around your way: Save on your commute with the TaxSaver Commuter Scheme, or hop on a bike with the Bike to Work Scheme.
• Grow with us: Learning never stops here. Everyone has a personal development plan to support their career growth.

Our Values & Shared Behaviours

We have five core values: We have a growth mindset. We like to simplify things and make things happen. We collaborate across teams, business units and brands. We’re passionate about what we do.

These values give us a framework for leadership and daily decision making. They’re brought to life by our shared behaviours, which define how we show up for our colleagues, our users and our customers:

• Create with Impact: we focus on work that makes a real difference.
• Play your Part: we own our contribution and support each other.
• Thrive Here: we build an environment where everyone can grow and do their best work.

We are a diverse bunch of people here in Distilled, and we want to continue to attract and retain a diverse range of people into our Company. We do not discriminate based on gender, marital status, family status, sexual orientation, religion, age, disability, race and membership of the Traveller community.