Data Engineer Manager
Artefact Open At a glance
Manager-level Data Engineering role at Artefact. APAC; Jakarta, Jakarta, Indonesia · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and tune data pipelines that move information between systems, using Python and SQL for ETL
- Look after databases and put reliable ways to store and retrieve data in place
- Use Azure, GCP or AWS to design and deploy scalable data solutions
- Work with teams to put machine-learning models into pipelines, and use Spark and Kafka for real-time processing
- Guide data engineers through mentoring and shared engineering practices
What you bring
- At least eight years working in data engineering
- Strong Python, SQL and database skills, plus hands-on work with ETL pipelines, cloud services, machine learning, Spark and Kafka
- Knowledge of data modelling and modern platform design, including building and maintaining platforms on Azure, AWS or GCP
- A bachelor's degree in computer science or another listed engineering field
- You already have authorization to work and are working in the market
Who this fits
This manager role suits someone who combines data engineering depth with business-facing communication and stakeholder collaboration. You’ll mentor engineers while working with teams on data and machine-learning pipelines.
From the employer
Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth.
The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner…
What you will be doing?
As a Data Engineer Manager, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data.
Your responsibilities will include:
- Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms.
- Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions.
- Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions.
- Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing.
- Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics.
- Mentor and guide engineers, fostering knowledge sharing and best practices.
What we are looking for?
- 8+ years of industry experience in data engineering.
- Proficiency in Python, SQL, and database management.
- Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP, AWS), ML Modeling, Spark & Kafka.
- Data modelling and modern data platform design concepts
- Building and maintaining data platforms in Azure/AWS or GCP
- Experience working with business stakeholders either internally or externally
- Excellent communication skills to collaborate effectively within teams and with stakeholders.
- Strong business acumen with an interest in business-facing roles.
- Adaptability and a start-up mentality to thrive in a dynamic environment.
- Minimum of a bachelor's degree in Computer Science, Electronics, and Communication Engineering degrees.
- Already have authorization to work and already working in the market
Artefact is the place to be: come and build the future of data and AI
Innovation: We have a passion for creating impacting projects and believe innovation can come from anyone.
Action: We make things rather than telling people how to make them.
Collaboration: We believe in bringing talented people together, winning together, and in learning from each other.
Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
Data Engineering
Find me workBy the team behind dataroles.