254 Data Engineer jobs in Indonesia

• Design, construct, install, test, and maintain highly scalable data management systems.
• Build and optimize robust ETL/ELT pipelines for data ingestion, transformation, and aggregation.
• Develop and maintain data warehouses and data lakes using modern big data technologies.
• Implement and manage data infrastructure on cloud platforms (AWS, Azure, GCP).
• Ensure data quality, consistency, and integrity across all data sources and systems.
• Collaborate with data scientists and analysts to understand their data needs and provide efficient data solutions.
• Optimize data query performance and data pipeline efficiency.
• Implement monitoring, alerting, and logging for data infrastructure.
• Develop and enforce data governance and security best practices.
• Stay current with emerging big data technologies and methodologies.
• Mentor junior data engineers and contribute to team knowledge sharing.
• Troubleshoot and resolve complex data-related issues in a timely manner.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• A minimum of 7 years of experience in data engineering, with a strong focus on big data technologies.
• Expertise in distributed data processing frameworks such as Apache Spark, Hadoop, Flink.
• Proficiency in programming languages like Python, Java, or Scala.
• Hands-on experience with cloud data services (e.g., AWS EMR, Glue, Redshift, S3; Azure Data Factory, Synapse; GCP Dataflow, BigQuery).
• Experience with SQL and NoSQL databases.
• Strong understanding of data modeling techniques and data warehousing concepts.
• Familiarity with containerization technologies like Docker and Kubernetes.
• Excellent problem-solving and debugging skills.
• Strong communication and collaboration skills, essential for a remote role.
• Experience with data pipeline orchestration tools (e.g., Airflow).
• Proven ability to work independently and manage complex projects.

• Designing, developing, and optimizing robust, scalable ETL/ELT pipelines for large-scale data processing.
• Building and managing data lakes, data warehouses, and other data storage solutions using cloud-based technologies (e.g., AWS, Azure, GCP).
• Implementing data modeling strategies to ensure efficient data storage, retrieval, and analysis.
• Collaborating with data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions.
• Developing and maintaining data quality frameworks and monitoring systems to ensure data integrity.
• Automating data processes and workflows to improve efficiency and reduce manual intervention.
• Evaluating and recommending new data technologies and tools to enhance our data infrastructure.
• Troubleshooting and resolving complex data-related issues, ensuring minimal downtime.
• Implementing data security and governance best practices.
• Mentoring junior data engineers and contributing to the team's technical growth.

Job Responsibilities

• Participate in the construction and development of data warehouses for financial projects, design models according to business requirements, and implement ETL.
• Provide data report support for business departments.
• Participate in optimizing ETL to improve code efficiency and reduce costs.

Job Qualifications

• Proficient in Spark, able to develop in Python and Scala, with good experience in performance tuning;
• Familiar with various data warehouse modeling theories, proficient in data model design and data layer design;
• Priority will be given to those with Tableau development experience;
• Priority will be given to those with a background in finance and e-commerce projects;
• Diligent, responsible, meticulous, with good team spirit, analytical skills, and communication skills.
• Key skills:
• Spark;
• Phyton;
• Scala;
• Dimensional Modelling.

Develop innovative data solutions that meet the evolving needs of the organization. Collaborate with cross-functional teams to identify and implement best practices in data management.

Monitor and optimize data pipelines for performance and reliability. Conduct regular data quality assessments and implement improvements as necessary.

Stay updated with the latest trends and technologies in data engineering to enhance team capabilities

Bachelor's Degree in relevant field of studies.

Develop innovative data solutions that meet the evolving needs of the organization. Collaborate with cross-functional teams to identify and implement best practices in data management.

Monitor and optimize data pipelines for performance and reliability. Conduct regular data quality assessments and implement improvements as necessary.

Stay updated with the latest trends and technologies in data engineering to enhance team capabilities

Bachelor's Degree in relevant field of studies.

• Devoteam is a leading consulting firm focused on digital strategy, tech platforms, and cybersecurity.

By combining creativity, tech, and data insights, we empower our customers to transform their business and unlock the future.

With 25 years' of experience and 8,000 employees across Europe and the Middle East, Devoteam promotes responsible tech for people and works to create better change.

#Creative Tech for Better Change

Devoteam has launched in January 2021 its new strategic plan, Infinite 2024, with the ambition to become the #1 EMEA partner of the leading Cloud-based platform companies (AWS, Google Cloud, Microsoft, Salesforce, ServiceNow), further reinforced by deep expertise in digital strategy, cybersecurity, and data.

The Data Engineer will be responsible for the following activities:

• Work closely with data architects and other stakeholders to design scalable and robust data architectures that meet the organization's requirements
• Develop and maintain data pipelines, which involve the extraction of data from various sources, data transformation to ensure quality and consistency, and loading the processed data into data warehouses or other storage systems
• Responsible for managing data warehouses and data lakes, ensuring their performance, scalability, and security
• Integrate data from different sources, such as databases, APIs, and external systems, to create unified and comprehensive datasets.
• Perform data transformations and implement Extract, Transform, Load (ETL) processes to convert raw data into formats suitable for analysis and reporting
• Collaborate with data scientists, analysts, and other stakeholders to establish data quality standards and implement data governance practices
• Optimise data processing and storage systems for performance and scalability

• Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements and deliver solutions

• Programming Skills: Proficiency in programming languages such as Python, Java, Scala, or SQL is essential for data engineering roles. Data engineers should have experience in writing efficient and optimized code for data processing, transformation, and integration.

• Database Knowledge: Strong knowledge of relational databases (e.g., SQL) and experience with database management systems (DBMS) is crucial. Familiarity with data modeling, schema design, and query optimization is important for building efficient data storage and retrieval systems.

• Big Data Technologies: Understanding and experience with big data technologies such as Apache Hadoop, Apache Spark, or Apache Kafka is highly beneficial. Knowledge of distributed computing and parallel processing frameworks is valuable for handling large-scale data processing.

• ETL and Data Integration: Proficiency in Extract, Transform, Load (ETL) processes and experience with data integration tools like Apache NiFi, Talend, or Informatica is desirable. Knowledge of data transformation techniques and data quality principles is important for ensuring accurate and reliable data.

• Data Warehousing: Familiarity with data warehousing concepts and experience with popular data warehousing platforms like Amazon Redshift, Google BigQuery, or Snowflake is advantageous. Understanding dimensional modeling and experience in designing and optimizing data warehouses is beneficial.

• Cloud Platforms: Knowledge of cloud computing platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) is increasingly important. Experience in deploying data engineering solutions in the cloud and utilizing cloud-based data services is valuable.

• Data Pipelines and Workflow Tools: Experience with data pipeline and workflow management tools such as Apache Airflow, Luigi, or Apache Oozie is beneficial. Understanding how to design, schedule, and monitor data workflows is essential for efficient data processing.

• Problem-Solving and Analytical Skills: Data engineers should have strong problem-solving abilities and analytical thinking to identify data-related issues, troubleshoot problems, and optimize data processing workflows.

• Communication and Collaboration: Effective communication and collaboration skills are crucial for working with cross-functional teams, including data scientists, analysts, and business stakeholders. Data engineers should be able to translate technical concepts into clear and understandable terms.

• Education and Experience

• Bachelor's degree in Engineering required.

• Minimum Two years of related experience is highly preferred.
• Two certifications in GCP (within 3 months after joining).

Status: Full-Time

Duration: -

Beginning date: September 2025

The Devoteam Group is committed to equal opportunities, promoting its employees on the basis of merit and actively fighting against all forms of discrimination. We believe that diversity contributes to the creativity, dynamism, and excellence of our organization. All our positions are open to people with disabilities.

PT. Entrepreneur Trust Digital provide clients with our professional team which are adapt with all the latest technologies. Our services in IT Outsourcing are an efficient way to deliver IT solutions to any business to boost business performance. We are looking for talented individuals for
Data Engineer
position

Requirements:

• Minimum 1-3 years of work experiences as Data Engineer/ETL Developer
• Minimum Associate/Bachelor degree level of education (D3/S1)
• Experience in SSIS and SQL Server
• Experience with Joins (Inner, Left, Right, Cross), Delete, Turncate, Drop Table, Execution Plan
• Familiar with programming language: C#, .Net, Java
• Able to work for bank company in Bintaro, Tangerang

Job type: Contract Fulltime Onsite- Jakarta, Working Onsite: Monday-Friday; WFO in Bintaro

a. Min experience
3 years as Data Engineer

b. Experience in writing
SQL query, SQL function and SQL procedure is mandatory

c. Experience in
Java development of API

is an advantage

d. Have experience in
SSRS reporting

,
PowerBI analytic, Google Big Query, ETL & data pipeline is mandatory.

e. Have knowledge and experience in data science with Python is an advantage