Junior Data Scientist
Data Engineer
Data Engineer
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Data Engineer Job Listings
Data Engineer (Data Infrastructure Engineer / Data Platform Engineer) job listings target candidates who can build and manage data pipelines and create reliable data platforms. Listings often highlight ETL/ELT processes, data warehouse architectures, real-time data pipelines, and cloud data services. Expectations around performance, scalability, and data security are clearly stated.
What Does a Data Engineer Do?
A Data Engineer collects and processes raw data, preparing it for analysis. They design data pipelines and automate ETL/ELT workflows. They build data warehouse and data lake architectures. They balance real-time streaming and batch processing. They manage schema design, data quality, and cataloging. By collaborating with analysts, data scientists, and product teams, they provide reliable and scalable data infrastructure.
What Should You Pay Attention to When Reviewing Data Engineer Job Listings?
Review the tech stack, data volume, and data velocity. The orchestration tools, messaging systems, and warehouse solutions should be clearly defined. Examine expectations for cloud providers, security standards, and cost optimization. Data governance, quality metrics, and SLA objectives should be transparent. Also consider code review culture, testing strategy, and deployment processes.
Required Education and Certifications in Data Engineer Job Listings
Degrees in Computer Engineering, Software Engineering, Industrial Engineering, or Management Information Systems are often preferred. Courses in databases, distributed systems, and cloud technologies are beneficial. Data-focused certifications on AWS, Azure, or GCP add strong value. SQL performance, data modeling, and security training are important. Open-source contributions and portfolio projects serve as strong evidence of capability.
What Skills Are Employers Looking For in Data Engineer Roles?
Analytical thinking and writing clean, testable code are expected. Working with large datasets, debugging, and performance tuning are critical skills. Communication and collaboration abilities are important. Familiarity with observability, monitoring, and alerting practices is preferred. Over time, data governance, data security, and cost awareness become increasingly important.
Career Opportunities for Data Engineers
There is high demand in e-commerce, finance, gaming, telecommunications, logistics, and health tech. Product companies, consulting firms, and SaaS providers offer broad opportunities. Career paths may evolve toward Senior Data Engineer, Data Platform Lead, Analytics Engineer, or Data Architect roles. Real-time analytics and machine learning platforms also open additional specialization areas.
How to Apply for Data Engineer Job Listings
Clearly specify the data pipelines you've built, the data volumes you've processed, and the tools you’ve used. Highlight improvements in latency, cost, and error rates with measurable metrics. Include code samples and repository links. In a technical cover letter, summarize your architectural decisions, testing approach, and how you handle failure scenarios. Prepare for interviews with system design and SQL practice.
Fields Data Engineers Can Work In
Data Engineers can work on batch and streaming processing, data warehouse and data lake design, event-driven architectures, and MLOps integrations. They build reliable data layers for BI teams. They enable infrastructure for areas such as fraud detection, recommendation systems, and customer analytics. They also play an active role in data governance and cataloging.
Programming Languages Commonly Required in Data Engineer Job Listings
Python, SQL, and Scala are the most commonly used languages. Java appears in some enterprise data pipelines. Apache Spark is widely used for distributed processing. Kafka and Flink stand out in messaging and streaming. Airflow and dbt are common choices for orchestration. Snowflake, BigQuery, and Redshift are popular in data warehousing. Familiarity with AWS, GCP, and Azure data services is expected. Knowledge of containers, CI/CD, and infrastructure automation adds value.
Junior Data Scientist
06.01.2026
Hollanda
Deneyim: 4-6 Yıl
Type of Work: Tam Zamanlı
Work Location: İş Yerinde
Department Level: Uzman
Job Description
We are looking for an experienced Data Scientist to drive one of our data science initiatives. The ideal candidate brings extensive expertise in statistical modeling, machine learning, and data analytics. In addition to technical proficiency, strong interpersonal skills are a must, as you will collaborate cross-functionally, and play a strong role in both developing and communicating analytic solutions.
The team
- Tribe Growth orchestrates the total relationship throughout a customer’s lifetime. With over 70 data analysts and scientists, we accelerate the transition towards becoming a fully data-driven organization and becoming the best mobile-led bank on the continent. We work in multi-disciplinary teams, allocated as data consultants both internally and externally to our tribe.
- At ING we promote diversity and want to make our teams a reflection of our world. If you recognize yourself in the description below, but your profile doesn't match the job description 100%, don't hesitate to apply.
Roles and responsibilities
- We value innovation and expect you to explore new use cases, contributing to our evolving data-driven strategies. Proficiency in data exploration, visualization, and storytelling is crucial for transforming complex findings into actionable insights for both technical and non-technical stakeholders. If you are a seasoned data scientist with a passion for innovation, ready to drive impactful insights and committed to personal growth, we want you on our team.
How to succeed
- We hire smart people like you for your potential. Our biggest expectation is that you’ll stay curious. Keep learning. Take on responsibility. In return, we’ll back you to develop into an even more awesome version of yourself.
- An MSc or Ph.D. with excellent academic results in the field of Computer Science, Machine Learning, Mathematics, Statistics, or other quantitative fields.
- 4+ years of relevant and demonstrable experience in the field of data science.
- Both broad and in-depth knowledge of machine Learning techniques: Classification, Regression, Clustering, Text Mining and Deep Learning.
- Experience with programming Languages and tools including Python, PySpark, SQL, Git, Shell.
- Familiarity with cloud platforms, particularly GCP and BigQuery is a plus.
- You embrace writing readable, documented and efficient code.
- You are not afraid to learn new technologies and help work through data engineering partnerships.
- Understanding of model lifecycles and monitoring including developing and bringing models to production.
- Demonstrated experience successfully collaborating in cross-functional teams including business, engineering and data science stakeholders.
- Experience in working in an Agile/Scrum is also a plus.
- You are open to feedback and growth on technical skills, business applications, and soft skills.
- You are fluent in written and spoken English. Dutch is a plus.
Rewards and benefits
- We want to make sure that it’s possible for you to strike the right balance between your career and your private life.
The benefits of working with us at ING include:
- 25-28 vacation days depending on contract
- Pension scheme
- 13th month salary
- 8% Holiday payment
- Hybrid working
- Personal growth and challenging work with endless possibilities
- An informal working environment with innovative colleagues
Candidate Criteria
Education Level: Lisans, Doktora
Language: İngilizce
University Department: Bilgisayar Bilimleri, Matematik, İstatistik
Skills
About Company
About ING Bank
Hakkımızda
Biz içinden geldiği gibi yaşayanların, kendi gibi olanların ING'siyiz.
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Biz sadece kolay, akıllı ve kişisel bir müşteri deneyimi yaratan zahmetsiz bankacılık anlayışımız ile insanları cesaretlendirmek, desteklemek ve güç vermek için buradayız.
