Saturday to Wednesday
-
Transportation -Loan -Bonus -Military Service Option -Health insurance
-Game room
-In-house Medical doctor
-Breakfast
-Occasional packages and gifts
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1001 - 5000 employees
Internet Provider / E-commerce / Online Services
توضیحات بیشتر
key Requirements
2 years experience in similar positionBachelor Computer and IT or Math / Statistics Microsoft SQL Server - Intermediate
PostgreSQL - Basic
Python - Intermediate
Linux - Basic
Apache Kafka - Intermediate
Apache Hadoop - Intermediate
Apache Airflow - Intermediate
Job Description
About the Role
We are looking for an experienced Data Engineer to join TAPSI’s Data Infrastructure team. You will be responsible for designing, developing, and maintaining scalable data platforms, pipelines, and infrastructure that support analytics, machine learning, and business applications across TAPSI.
In this role, you will work on building reliable data ingestion systems, optimizing large-scale data processing workflows, improving platform performance, and enabling teams across TAPSI to efficiently access and utilize data.
The ideal candidate has strong data engineering fundamentals, experience working with distributed data systems, and enjoys solving complex infrastructure and data challenges at scale.
Responsibilities
As part of the Data Infrastructure team, you will contribute to systems such as:
We are looking for an experienced Data Engineer to join TAPSI’s Data Infrastructure team. You will be responsible for designing, developing, and maintaining scalable data platforms, pipelines, and infrastructure that support analytics, machine learning, and business applications across TAPSI.
In this role, you will work on building reliable data ingestion systems, optimizing large-scale data processing workflows, improving platform performance, and enabling teams across TAPSI to efficiently access and utilize data.
The ideal candidate has strong data engineering fundamentals, experience working with distributed data systems, and enjoys solving complex infrastructure and data challenges at scale.
Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL/ELT workflows for batch and streaming data processing.
- Build and operate large-scale data processing systems using technologies such as Apache Spark, Hadoop, HDFS, YARN, and Kafka.
- Develop reliable data ingestion pipelines to collect data from various sources, including databases, applications, and external systems.
- Build and maintain data workflows using orchestration tools such as Apache Airflow.
- Improve the reliability, scalability, and performance of existing data infrastructure and processing jobs.
- Optimize Spark applications, SQL queries, storage formats, and data processing strategies for large datasets.
- Design and maintain data models, transformations, and processing frameworks used by analytics and machine learning teams.
- Build internal data infrastructure tools and frameworks that improve data accessibility and engineering productivity.
- Monitor, troubleshoot, and resolve issues across data pipelines, distributed systems, and production data platforms.
- Perform root cause analysis for data quality issues, pipeline failures, performance bottlenecks, and infrastructure problems.
- Collaborate with Data Scientists, Analysts, ML Engineers, Backend Engineers, and Platform teams to deliver reliable data solutions.
- Evaluate and introduce new technologies and best practices to improve TAPSI’s data platform capabilities.
- Maintain and optimize databases, including indexing, partitioning, query optimization, and operational maintenance.
- Minimum 2 years of professional experience in Data Engineering, Data Infrastructure, Big Data, or related engineering roles.
- Bachelor’s degree in Computer Engineering, Computer Science, Mathematics, or another quantitative field.
- Strong programming skills in Python with a good understanding of software engineering principles.
- Solid experience with SQL and relational databases.
- Hands-on experience with big data technologies such as Apache Spark, Hadoop ecosystem (HDFS, YARN, Hive), and Apache Kafka.
- Experience designing and maintaining data pipelines and ETL/ELT processes.
- Experience with workflow orchestration tools such as Apache Airflow.
- Experience working with large-scale datasets and distributed processing systems.
- Familiarity with database technologies such as PostgreSQL, MongoDB, or similar systems.
- Understanding of data warehouse concepts, data modeling, partitioning, and optimization techniques.
- Experience debugging and troubleshooting production data systems.
- Strong analytical and problem-solving skills.
- Ability to work effectively with cross-functional engineering and business teams.
- Familiarity with Linux environments and production system operations.
- Experience operating production data platforms and distributed systems.
- Experience with streaming data architectures and real-time processing.
- Experience with Spark optimization and performance tuning.
- Experience with Hadoop cluster operations and resource management.
- Familiarity with containerized environments and Kubernetes.
- Experience with Infrastructure as Code and GitOps practices.
- Experience building internal data platform frameworks and developer tools.
- Experience with data quality frameworks, monitoring, and observability solutions.
As part of the Data Infrastructure team, you will contribute to systems such as:
- Enterprise-scale data processing platforms.
- Batch and streaming data pipelines.
- Data warehouse and analytical infrastructure.
- Distributed storage and compute systems.
- Data workflow orchestration platforms.
- Internal tools enabling Data Analysts, Data Scientists, and ML teams.
- Reliable foundations for TAPSI’s analytics and machine learning ecosystem.
Job Requirements
Gender
Men / Women
Education
Software
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