Software Data Engineer

Devsinc is seeking a talented Data Engineer having minimum of 2 years of professional experience to join our growing data this role you will design and build scalable data pipelines work with modern cloud platforms and lay the foundation for analytics that drive critical business decisions. From day one youll learn from senior engineers work with a modern cloud stack and see your contributions make a tangible impact.

Responsibilities:

• Design develop and maintain automated ETL/ELT data pipelines for structured and unstructured datasets.
• Build and optimize scalable secure and cost-efficient cloud data solutions using AWS Azure or GCP.
• Model cleanse and transform data to support analytics dashboards and reporting use-cases.
• Implement automated testing monitoring and alerting to ensure high data quality and reliability.
• Develop high-performance Python-based services and utilities for data ingestion and processing.
• Work with APIs event-driven systems and streaming platforms for real-time data workflows.
• Collaborate with cross-functional teams (Data Science Backend DevOps Product) to gather requirements and deliver tailored data solutions.
• Follow strong software engineering best practices clean code modularity version control CI/CD.
• Document architecture data flows schemas and development standards.
• Stay updated on evolving data engineering tools frameworks and cloud-native technologies.

• Bachelors degree in Computer Science Software Engineering or a related field.
• Minimum 2 years of professional experience.
• Strong knowledge of Python and SQL for data processing and transformation.
• Hands-on experience with at least one major cloud platform AWS GCP or Azure.
• Exposure to cloud-native data services such as AWS Glue Redshift Azure Data Factory BigQuery Synapse etc.
• Familiarity with modern data warehouses Snowflake Redshift BigQuery or Synapse.
• Strong understanding of ETL/ELT frameworks such as dbt Apache Spark or Databricks.
• Experience working with orchestration tools like Apache Airflow Azure Data Factory Pipelines or AWS Glue Workflows.
• Proficiency with version control systems (GitHub GitLab Bitbucket) and CI/CD pipelines.
• Solid understanding of Data Lake architectures (S3 ADLS GCS) and schema design principles.
• Basic understanding of data governance security compliance and access management concepts.
• Familiarity with streaming platforms such as Kafka Amazon Kinesis or Google Pub/Sub.
• Collaborative open to knowledge-sharing and teamwork.
• Team Player willing to support peers and contribute to collective success.
• Growth Minded eager to learn improve and adapt to emerging technologies.
• Adaptable flexible in dynamic fast-paced environments.
• Customer-Centric focused on delivering solutions that create real business value.