Junior Data Engineer (Databricks) Job at Addepto sp. z o.o.

Senior Databricks Data Engineer

To develop, implement, and optimize complex Data Warehouse (DWH) and Data Lakeho...

Location

Romania , Bucharest

Salary:

Not provided

Inetum

Expiration Date

Until further notice

Requirements

Proven, expert-level experience with the entire Databricks ecosystem (Workspace, Cluster Management, Notebooks, Databricks SQL)
In-depth knowledge of Spark architecture (RDD, DataFrames, Spark SQL) and advanced optimization techniques
Expertise in implementing and managing Delta Lake (ACID properties, Time Travel, Merge, Optimize, Vacuum)
Advanced/expert-level proficiency in Python (with PySpark) and/or Scala (with Spark)
Advanced/expert-level skills in SQL and Data Modeling (Dimensional, 3NF, Data Vault)
Solid experience with a major Cloud platform (AWS, Azure, or GCP), especially with storage services (S3, ADLS Gen2, GCS) and networking.

Job Responsibility

Design and implement robust, scalable, and high-performance ETL/ELT data pipelines using PySpark/Scala and Databricks SQL on the Databricks platform
Expertise in implementing and optimizing the Medallion architecture (Bronze, Silver, Gold) using Delta Lake to ensure data quality, consistency, and historical tracking
Efficient implementation of the Lakehouse architecture on Databricks, combining best practices from DWH and Data Lake
Optimize Databricks clusters, Spark operations, and Delta tables to reduce latency and computational costs
Design and implement real-time/near-real-time data processing solutions using Spark Structured Streaming and Delta Live Tables
Implement and manage Unity Catalog for centralized data governance, data security and data lineage
Define and implement data quality standards and rules to maintain data integrity
Develop and manage complex workflows using Databricks Workflows or external tools to automate pipelines
Integrate Databricks pipelines into CI/CD processes
Work closely with Data Scientists, Analysts, and Architects to understand business requirements and deliver optimal technical solutions

What we offer

Full access to foreign language learning platform
Personalized access to tech learning platforms
Tailored workshops and trainings to sustain your growth
Medical insurance
Meal tickets
Monthly budget to allocate on flexible benefit platform
Access to 7 Card services
Wellbeing activities and gatherings.

Fulltime

Senior Databricks Data Engineer

To develop, implement, and optimize complex Data Warehouse (DWH) and Data Lakeho...

Location

Romania , Bucharest

Salary:

Not provided

Inetum

Expiration Date

Until further notice

Requirements

Proven, expert-level experience with the entire Databricks ecosystem (Workspace, Cluster Management, Notebooks, Databricks SQL)
in-depth knowledge of Spark architecture (RDD, DataFrames, Spark SQL) and advanced optimization techniques
expertise in implementing and managing Delta Lake (ACID properties, Time Travel, Merge, Optimize, Vacuum)
advanced/expert-level proficiency in Python (with PySpark) and/or Scala (with Spark)
advanced/expert-level skills in SQL and Data Modeling (Dimensional, 3NF, Data Vault)
solid experience with a major Cloud platform (AWS, Azure, or GCP), especially with storage services (S3, ADLS Gen2, GCS) and networking
bachelor’s degree in Computer Science, Engineering, Mathematics, or a relevant technical field
minimum of 5+ years of experience in Data Engineering, with at least 3+ years of experience working with Databricks and Spark at scale.

Job Responsibility

Design and implement robust, scalable, and high-performance ETL/ELT data pipelines using PySpark/Scala and Databricks SQL on the Databricks platform
expertise in implementing and optimizing the Medallion architecture (Bronze, Silver, Gold) using Delta Lake
design and implement real-time/near-real-time data processing solutions using Spark Structured Streaming and Delta Live Tables (DLT)
implement Unity Catalog for centralized data governance, fine-grained security (row/column-level security), and data lineage
develop and manage complex workflows using Databricks Workflows (Jobs) or external tools (Azure Data Factory, Airflow) to automate pipelines
integrate Databricks pipelines into CI/CD processes using tools like Git, Databricks Repos, and Bundles
work closely with Data Scientists, Analysts, and Architects to deliver optimal technical solutions
provide technical guidance and mentorship to junior developers.

What we offer

Full access to foreign language learning platform
personalized access to tech learning platforms
tailored workshops and trainings to sustain your growth
medical insurance
meal tickets
monthly budget to allocate on flexible benefit platform
access to 7 Card services
wellbeing activities and gatherings.

Fulltime

Lead Data Engineer

As a Lead Data Engineer at Rearc, you'll play a pivotal role in establishing and...

Location

India , Bengaluru

Salary:

Not provided

Rearc

Expiration Date

Until further notice

Requirements

10+ years of experience in data engineering, data architecture, or related fields
Extensive experience in writing and testing Java and/or Python
Proven experience with data pipeline orchestration using platforms such as Airflow, Databricks, DBT or AWS Glue
Hands-on experience with data analysis tools and libraries like Pyspark, NumPy, Pandas, or Dask
Proficiency with Spark and Databricks is highly desirable
Proven track record of leading complex data engineering projects, including designing and implementing scalable data solutions
Hands-on experience with ETL processes, data warehousing, and data modeling tools
In-depth knowledge of data integration tools and best practices
Strong understanding of cloud-based data services and technologies (e.g., AWS Redshift, Azure Synapse Analytics, Google BigQuery)
Strong strategic and analytical skills

Job Responsibility

Understand Requirements and Challenges: Collaborate with stakeholders to deeply understand their data requirements and challenges
Implement with a DataOps Mindset: Embrace a DataOps mindset and utilize modern data engineering tools and frameworks, such as Apache Airflow, Apache Spark, or similar, to build scalable and efficient data pipelines and architectures
Lead Data Engineering Projects: Take the lead in managing and executing data engineering projects, providing technical guidance and oversight to ensure successful project delivery
Mentor Data Engineers: Share your extensive knowledge and experience in data engineering with junior team members, guiding and mentoring them to foster their growth and development in the field
Promote Knowledge Sharing: Contribute to our knowledge base by writing technical blogs and articles, promoting best practices in data engineering, and contributing to a culture of continuous learning and innovation

Senior Data Engineer

At Rearc, we're committed to empowering engineers to build awesome products and ...

Location

India , Bangalore

Salary:

Not provided

Rearc

Expiration Date

Until further notice

Requirements

8+ years of experience in data engineering, showcasing expertise in diverse architectures, technology stacks, and use cases
Strong expertise in designing and implementing data warehouse and data lake architectures, particularly in AWS environments
Extensive experience with Python for data engineering tasks, including familiarity with libraries and frameworks commonly used in Python-based data engineering workflows
Proven experience with data pipeline orchestration using platforms such as Airflow, Databricks, DBT or AWS Glue
Hands-on experience with data analysis tools and libraries like Pyspark, NumPy, Pandas, or Dask
Proficiency with Spark and Databricks is highly desirable
Experience with SQL and NoSQL databases, including PostgreSQL, Amazon Redshift, Delta Lake, Iceberg and DynamoDB
In-depth knowledge of data architecture principles and best practices, especially in cloud environments
Proven experience with AWS services, including expertise in using AWS CLI, SDK, and Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or AWS CDK
Exceptional communication skills, capable of clearly articulating complex technical concepts to both technical and non-technical stakeholders

Job Responsibility

Strategic Data Engineering Leadership: Provide strategic vision and technical leadership in data engineering, guiding the development and execution of advanced data strategies that align with business objectives
Architect Data Solutions: Design and architect complex data pipelines and scalable architectures, leveraging advanced tools and frameworks (e.g., Apache Kafka, Kubernetes) to ensure optimal performance and reliability
Drive Innovation: Lead the exploration and adoption of new technologies and methodologies in data engineering, driving innovation and continuous improvement across data processes
Technical Expertise: Apply deep expertise in ETL processes, data modelling, and data warehousing to optimize data workflows and ensure data integrity and quality
Collaboration and Mentorship: Collaborate closely with cross-functional teams to understand requirements and deliver impactful data solutions—mentor and coach junior team members, fostering their growth and development in data engineering practices
Thought Leadership: Contribute to thought leadership in the data engineering domain through technical articles, conference presentations, and participation in industry forums

Data Engineer

We are looking for an experienced Data Engineer with deep expertise in Databrick...

Location

Salary:

Not provided

Coherent Solutions

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field
5+ years of experience in data engineering, with at least 2 years of hands-on experience with Databricks (including Spark, Delta Lake, and MLflow)
Strong proficiency in Python and/or Scala for data processing
Deep understanding of distributed data processing, data warehousing, and ETL concepts
Experience with cloud data platforms (Azure Data Lake, AWS S3, or Google Cloud Storage)
Solid knowledge of SQL and experience with large-scale relational and NoSQL databases
Familiarity with CI/CD, DevOps, and infrastructure-as-code practices for data engineering
Experience with data governance, security, and compliance in cloud environments
Excellent problem-solving, communication, and leadership skills
English: Upper Intermediate level or higher

Job Responsibility

Lead the design, development, and deployment of scalable data pipelines and ETL processes using Databricks (Spark, Delta Lake, MLflow)
Architect and implement data lakehouse solutions, ensuring data quality, governance, and security
Optimize data workflows for performance and cost efficiency on Databricks and cloud platforms (Azure, AWS, or GCP)
Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights
Mentor and guide junior engineers, promoting best practices in data engineering and Databricks usage
Develop and maintain documentation, data models, and technical standards
Monitor, troubleshoot, and resolve issues in production data pipelines and environments
Stay current with emerging trends and technologies in data engineering and Databricks ecosystem

What we offer

Technical and non-technical training for professional and personal growth
Internal conferences and meetups to learn from industry experts
Support and mentorship from an experienced employee to help you professional grow and development
Internal startup incubator
Health insurance
English courses
Sports activities to promote a healthy lifestyle
Flexible work options, including remote and hybrid opportunities
Referral program for bringing in new talent
Work anniversary program and additional vacation days

Senior Azure Data Engineer

Seeking a Lead AI DevOps Engineer to oversee design and delivery of advanced AI/...

Location

Poland

Salary:

Not provided

Lingaro

Expiration Date

Until further notice

Requirements

At least 6 years of professional experience in the Data & Analytics area
1+ years of experience (or acting as) in the Senior Consultant or above role with a strong focus on data solutions build in Azure and Databricks/Synapse/(MS Fabric is nice to have)
Proven experience in Azure cloud-based infrastructure, Databricks and one of SQL implementation (e.g., Oracle, T-SQL, MySQL, etc.)
Proficiency in programming languages such as SQL, Python, PySpark is essential (R or Scala nice to have)
Very good level of communication including ability to convey information clearly and specifically to co-workers and business stakeholders
Working experience in the agile methodologies – supporting tools (JIRA, Azure DevOps)
Experience in leading and managing a team of data engineers, providing guidance, mentorship, and technical support
Knowledge of data management principles and best practices, including data governance, data quality, and data integration
Good project management skills, with the ability to prioritize tasks, manage timelines, and deliver high-quality results within designated deadlines
Excellent problem-solving and analytical skills, with the ability to identify and resolve complex data engineering issues

Job Responsibility

Act as a senior member of the Data Science & AI Competency Center, AI Engineering team, guiding delivery and coordinating workstreams
Develop and execute a cloud data strategy aligned with organizational goals
Lead data integration efforts, including ETL processes, to ensure seamless data flow
Implement security measures and compliance standards in cloud environments
Continuously monitor and optimize data solutions for cost-efficiency
Establish and enforce data governance and quality standards
Leverage Azure services, as well as tools like dbt and Databricks, for efficient data pipelines and analytics solutions
Work with cross-functional teams to understand requirements and provide data solutions
Maintain comprehensive documentation for data architecture and solutions
Mentor junior team members in cloud data architecture best practices

What we offer

Stable employment
“Office as an option” model
Workation
Great Place to Work® certified employer
Flexibility regarding working hours and your preferred form of contract
Comprehensive online onboarding program with a “Buddy” from day 1
Cooperation with top-tier engineers and experts
Unlimited access to the Udemy learning platform from day 1
Certificate training programs
Upskilling support

Senior Data Engineer

At Ingka Investments (Part of Ingka Group – the largest owner and operator of IK...

Location

Netherlands , Leiden

Salary:

Not provided

IKEA

Expiration Date

Until further notice

Requirements

Formal qualifications (BSc, MSc, PhD) in computer science, software engineering, informatics or equivalent
Minimum 3 years of professional experience as a (Junior) Data Engineer
Strong knowledge in designing efficient, robust and automated data pipelines, ETL workflows, data warehousing and Big Data processing
Hands-on experience with Azure data services like Azure Databricks, Unity Catalog, Azure Data Lake Storage, Azure Data Factory, DBT and Power BI
Hands-on experience with data modeling for BI & ML for performance and efficiency
The ability to apply such methods to solve business problems using one or more Azure Data and Analytics services in combination with building data pipelines, data streams, and system integration
Experience in driving new data engineering developments (e.g. apply new cutting edge data engineering methods to improve performance of data integration, use new tools to improve data quality and etc.)
Knowledge of DevOps practices and tools including CI/CD pipelines and version control systems (e.g., Git)
Proficiency in programming languages such as Python, SQL, PySpark and others relevant to data engineering
Hands-on experience to deploy code artifacts into production

Job Responsibility

Contribute to the development of D&A platform and analytical tools, ensuring easy and standardized access and sharing of data
Subject matter expert for Azure Databrick, Azure Data factory and ADLS
Help design, build and maintain data pipelines (accelerators)
Document and make the relevant know-how & standard available
Ensure pipelines and consistency with relevant digital frameworks, principles, guidelines and standards
Support in understand needs of Data Product Teams and other stakeholders
Explore ways create better visibility on data quality and Data assets on the D&A platform
Identify opportunities for data assets and D&A platform toolchain
Work closely together with partners, peers and other relevant roles like data engineers, analysts or architects across IKEA as well as in your team

What we offer

Opportunity to develop on a cutting-edge Data & Analytics platform
Opportunities to have a global impact on your work
A team of great colleagues to learn together with
An environment focused on driving business and personal growth together, with focus on continuous learning

Fulltime

Senior Data Engineer

Senior Data Engineer – Dublin (Hybrid) Contract Role | 3 Days Onsite. We are see...

Location

Ireland , Dublin

Salary:

Not provided

Solas IT Recruitment

Expiration Date

Until further notice

Requirements

7+ years of experience as a Data Engineer working with distributed data systems
4+ years of deep Snowflake experience, including performance tuning, SQL optimization, and data modelling
Strong hands-on experience with the Hadoop ecosystem: HDFS, Hive, Impala, Spark (PySpark preferred)
Oozie, Airflow, or similar orchestration tools
Proven expertise with PySpark, Spark SQL, and large-scale data processing patterns
Experience with Databricks and Delta Lake (or equivalent big-data platforms)
Strong programming background in Python, Scala, or Java
Experience with cloud services (AWS preferred): S3, Glue, EMR, Redshift, Lambda, Athena, etc.

Job Responsibility

Build, enhance, and maintain large-scale ETL/ELT pipelines using Hadoop ecosystem tools including HDFS, Hive, Impala, and Oozie/Airflow
Develop distributed data processing solutions with PySpark, Spark SQL, Scala, or Python to support complex data transformations
Implement scalable and secure data ingestion frameworks to support both batch and streaming workloads
Work hands-on with Snowflake to design performant data models, optimize queries, and establish solid data governance practices
Collaborate on the migration and modernization of current big-data workloads to cloud-native platforms and Databricks
Tune Hadoop, Spark, and Snowflake systems for performance, storage efficiency, and reliability
Apply best practices in data modelling, partitioning strategies, and job orchestration for large datasets
Integrate metadata management, lineage tracking, and governance standards across the platform
Build automated validation frameworks to ensure accuracy, completeness, and reliability of data pipelines
Develop unit, integration, and end-to-end testing for ETL workflows using Python, Spark, and dbt testing where applicable

Junior Data Engineer (Databricks)

Addepto sp. z o.o.

Location:
Poland

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Requirements:

Additional Information:

Job Posted:
January 11, 2026

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