Data Engineer (AWS)
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Job Description
This role is for one of our clients
Company Name: Muoro.io
Industry: Technology, Information and Media
Seniority level: Mid-Senior level
Min Experience: 5 years
Location: NCR
JobType: full-time
We are seeking an experienced Data Engineer with deep expertise in the AWS data ecosystem to design, build, and optimize scalable data pipelines and platforms. The ideal candidate will have strong analytical skills, hands-on experience in modern data architectures, and a passion for delivering high-quality, reliable data solutions.
Key Responsibilities
Design, develop, and maintain robust data pipelines and ETL workflows using AWS tools such as Glue, Kinesis, Redshift, S3, and Data Lake architectures.
Work extensively with SQL and Databricks to process, transform, and analyze large datasets.
Implement data orchestration and workflow automation using tools like Airflow or Step Functions.
Ensure data quality, integrity, and consistency across systems through rigorous validation and monitoring practices.
Collaborate with cross-functional teams, including data analysts and software engineers, to support data-driven decision-making.
Optimize data storage, retrieval, and processing for scalability and performance in a cloud-native environment.
Requirements
5+ years of hands-on experience in data engineering.
Proven expertise in the AWS ecosystem (Glue, Kinesis, Redshift, S3).
Proficiency in SQL, Databricks, and data pipeline orchestration tools.
Strong understanding of data analysis, data quality management, and data modeling principles.
Experience working with data lakes and modern data architectures.
Excellent problem-solving, communication, and collaboration skills.
Core Skills
SQL
AWS (Glue, Kinesis, Redshift, S3)
Databricks
Data Pipeline Development
Airflow / Step Functions
Data Quality Management
Data Lake Architecture
Company Name: Muoro.io
Industry: Technology, Information and Media
Seniority level: Mid-Senior level
Min Experience: 5 years
Location: NCR
JobType: full-time
We are seeking an experienced Data Engineer with deep expertise in the AWS data ecosystem to design, build, and optimize scalable data pipelines and platforms. The ideal candidate will have strong analytical skills, hands-on experience in modern data architectures, and a passion for delivering high-quality, reliable data solutions.
Key Responsibilities
Design, develop, and maintain robust data pipelines and ETL workflows using AWS tools such as Glue, Kinesis, Redshift, S3, and Data Lake architectures.
Work extensively with SQL and Databricks to process, transform, and analyze large datasets.
Implement data orchestration and workflow automation using tools like Airflow or Step Functions.
Ensure data quality, integrity, and consistency across systems through rigorous validation and monitoring practices.
Collaborate with cross-functional teams, including data analysts and software engineers, to support data-driven decision-making.
Optimize data storage, retrieval, and processing for scalability and performance in a cloud-native environment.
Requirements
5+ years of hands-on experience in data engineering.
Proven expertise in the AWS ecosystem (Glue, Kinesis, Redshift, S3).
Proficiency in SQL, Databricks, and data pipeline orchestration tools.
Strong understanding of data analysis, data quality management, and data modeling principles.
Experience working with data lakes and modern data architectures.
Excellent problem-solving, communication, and collaboration skills.
Core Skills
SQL
AWS (Glue, Kinesis, Redshift, S3)
Databricks
Data Pipeline Development
Airflow / Step Functions
Data Quality Management
Data Lake Architecture
More Info
Job Type:
Industry:
Function:
Employment Type:
Key Skills
Data Lake Architecture
Data Pipeline Development
Data Quality Management
About Company
Skills:
Sql, Databricks, S3, AWS Glue, Kinesis, Redshift, Data Quality Management, Data Lake Architecture, Step Functions, Data Pipeline Development, Airflow
Skills:
Data Integration, Sql, AWS, Pl Sql, Data Warehousing, Oracle, Etl Tools, Informatica, Database Development, ETL processes, backend database systems
Skills:
Nosql, Terraform, Docker, Spark, Kafka, Data Warehousing, Sql, Python, AWS, Etl
Skills:
snowflake , Star Schema, Python, Sql, Etl, Advanced SQL querying, Snowflake schema
Skills:
Apache Airflow, Aws Lambda, Bitbucket, AWS Glue, Gitlab, Python, Sql, AWS, Aws S3, AWS Step Functions