Senior Data Engineer

L&T Technology Services; Göteborgs kommun; On-site; SEK 700,000 - 900,000; Full time

Job summary

L&T Technology Services Gothenburg, Sweden, is seeking a Senior Data Engineer to design, develop, and maintain scalable batch and streaming data pipelines. You will ingest data into cloud platforms, build ETL/ELT workflows, and implement data quality checks across AWS, Azure, and Power BI ecosystems.

Applicants should have 5+ years in Data Engineering, strong Python/SQL skills, and hands-on Spark expertise. Experience with Databricks/Snowflake, Kafka, and data governance is a plus.

Qualifications

• 5+ years of professional experience in Data Engineering.
• Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or equivalent.
• Strong hands-on experience with Python and/or SQL.
• Strong knowledge of Apache Spark and big-data processing.
• Experience with Kafka; knowledge of Apache Flink is an advantage.
• Strong understanding of Data Lakes, Data Warehousing, ETL/ELT, and data modelling.
• Hands-on experience with Databricks and/or Snowflake.
• Strong experience with AWS data services.
• Experience with Azure Data Factory and Azure data services.
• Experience with Power BI for data analysis and visualization.
• Good knowledge of DevOps, CI/CD, automated testing, and release processes.
• Understanding of data quality, monitoring, security, and governance.

Responsibilities

• Design, develop, and maintain scalable batch and streaming data pipelines.
• Ingest data from multiple sources into cloud-based data platforms and data lakes.
• Develop data processing workflows for cleansing, deduplication, transformation, and enrichment.
• Build and maintain ETL/ELT pipelines using technologies such as Spark, Kafka, and Databricks.
• Work with AWS data services including S3, Redshift, and EMR.
• Support Azure data services, particularly Azure Data Factory and Power BI.
• Implement data quality checks to ensure accuracy, completeness, consistency, and security.

Skills

Batch data pipelines

Streaming data pipelines

Python

SQL

Apache Spark

Kafka

Databricks

Snowflake

AWS data services

Azure Data Factory

Power BI

Data Lakes

Data Warehousing

ETL/ELT

Data modelling

CI/CD

DevOps

Data governance

Education

Bachelor's or Master's in CS/Engineering/IT

Tools

Databricks

Snowflake

Kafka

Azure Data Factory

Power BI

AWS data services

Job description

L&T Technology Services Limited (LTTS) is a global leader in Engineering and R&D (ER&D) services. With 719 patents filed for 57 of the Global Top 100 ER&D spenders, LTTS lives and breathes engineering. Our innovations speak for themselves – World’s 1st Autonomous Welding Robot, Solar ‘Connectivity’ Drone, and the Smartest Campus in the World, to name a few

.LTTS’ expertise in engineering design, product development, smart manufacturing, and digitalization touches every area of human lives - from the moment one wakes up till the time one goes to bed. With 69 Innovation and R&D design centres globally, we specialize in disruptive technology spaces such as 5G, Artificial Intelligence, Collaborative Robots, Digital Factory, and Autonomous Transport

We are looking for someone with key skills and able to perform the following roles & responsibilities :-

Gothenburg, Sweden

Role Summary:

Key Responsibilities

• Design, develop, and maintain scalable batch and streaming data pipelines.
• Ingest data from multiple sources into cloud-based data platforms and data lakes.
• Develop data processing workflows for cleansing, deduplication, transformation, and enrichment.
• Build and maintain ETL/ELT pipelines using technologies such as Spark, Kafka, and Databricks.
• Work with AWS data services including S3, Redshift, and EMR.
• Support Azure data services, particularly Azure Data Factory and Power BI.
• Implement data quality checks to ensure accuracy, completeness, consistency, and security.

Required Skills & Experience

• 5+ years of professional experience in Data Engineering.
• Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or equivalent experience.
• Strong hands-on experience with Python and/or SQL.
• Strong knowledge of Apache Spark and big-data processing.
• Experience with Kafka; knowledge of Apache Flink is an advantage.
• Strong understanding of Data Lakes, Data Warehousing, ETL/ELT, and data modelling.
• Hands-on experience with Databricks and/or Snowflake.
• Strong experience with AWS data services.
• Experience with Azure Data Factory and Azure data services.
• Experience with Power BI for data analysis and visualization.
• Good knowledge of DevOps, CI/CD, automated testing, and release processes.
• Understanding of data quality, monitoring, security, and governance.