Software Data Engineer

As a Software Data Engineer specializing in AWS and Python, you will be an integral part of our team in Mumbai. Your primary responsibility will be to design, build, and maintain scalable data pipelines and infrastructure on AWS, facilitating data-driven decision-making within the organization. You will collaborate closely with data scientists, analysts, and software engineers to deliver robust data solutions using Python and cloud-native technologies. Key Responsibilities: - Design, develop, and maintain scalable ETL/ELT data pipelines on AWS cloud infrastructure - Build and optimize data ingestion, transformation, and storage workflows - Develop reusable Python scripts and modules to automate data engineering tasks - Utilize AWS services such as S3, Glue, Lambda, Redshift, EMR, and related tools - Ensure data quality, integrity, and reliability across all data systems - Collaborate with cross-functional teams to understand data requirements and translate them into technical solutions - Monitor, troubleshoot, and improve existing data infrastructure for performance and scalability - Document data pipelines, data models, and engineering processes - Participate in code reviews and contribute to engineering best practices Requirements & Qualifications: - 2 to 5 years of hands-on experience in data engineering or a related software engineering role - Strong proficiency in Python for data processing and pipeline development - Solid experience with AWS cloud services (S3, Glue, Lambda, Redshift, EMR, Kinesis, or similar) - Experience working with SQL and relational/non-relational databases - Familiarity with data warehousing concepts and big data frameworks (Spark, Hadoop, etc.) - Understanding of data modeling, schema design, and ETL/ELT best practices - Experience with version control systems such as Git - Excellent problem-solving skills and attention to detail - Strong communication and teamwork abilities - Experience with CI/CD pipelines and infrastructure-as-code tools is a plus - Exposure to Apache Airflow or similar workflow orchestration tools is advantageous In addition to the technical aspects of the role, it's worth noting that Smart Working is a forward-thinking technology and staffing solutions company. We focus on connecting skilled professionals with innovative organizations in the IT and data engineering space. Our commitment lies in fostering smart, flexible work environments and delivering high-quality talent solutions to our clients. As a Software Data Engineer specializing in AWS and Python, you will be an integral part of our team in Mumbai. Your primary responsibility will be to design, build, and maintain scalable data pipelines and infrastructure on AWS, facilitating data-driven decision-making within the organization. You will collaborate closely with data scientists, analysts, and software engineers to deliver robust data solutions using Python and cloud-native technologies. Key Responsibilities: - Design, develop, and maintain scalable ETL/ELT data pipelines on AWS cloud infrastructure - Build and optimize data ingestion, transformation, and storage workflows - Develop reusable Python scripts and modules to automate data engineering tasks - Utilize AWS services such as S3, Glue, Lambda, Redshift, EMR, and related tools - Ensure data quality, integrity, and reliability across all data systems - Collaborate with cross-functional teams to understand data requirements and translate them into technical solutions - Monitor, troubleshoot, and improve existing data infrastructure for performance and scalability - Document data pipelines, data models, and engineering processes - Participate in code reviews and contribute to engineering best practices Requirements & Qualifications: - 2 to 5 years of hands-on experience in data engineering or a related software engineering role - Strong proficiency in Python for data processing and pipeline development - Solid experience with AWS cloud services (S3, Glue, Lambda, Redshift, EMR, Kinesis, or similar) - Experience working with SQL and relational/non-relational databases - Familiarity with data warehousing concepts and big data frameworks (Spark, Hadoop, etc.) - Understanding of data modeling, schema design, and ETL/ELT best practices - Experience with version control systems such as Git - Excellent problem-solving skills and attention to detail - Strong communication and teamwork abilities - Experience with CI/CD pipelines and infrastructure-as-code tools is a plus - Exposure to Apache Airflow or similar workflow orchestration tools is advantageous In addition to the technical aspects of the role, it's worth noting that Smart Working is a forward-thinking technology and staffing solutions company. We focus on connecting skilled professionals with innovative organizations in the IT and data engineering space. Our commitment lies in fostering smart, flexible work environments and delivering high-quality talent solutions to our c