Data Engineering Specialist

19 hours ago

guntur, India beBeeDataEngineer Full time

OverviewWe are seeking a skilled professional to contribute to the design and development of data systems, including pipelines, APIs, analytics, AI, and machine learning at scale.The ideal candidate will have hands-on experience in writing high-quality, scalable, and maintainable code across data pipelines, APIs, and data platform services. They will also collaborate with senior engineers, analysts, and product stakeholders to translate technical requirements into working solutions.Main Responsibilities:Writing high-quality, scalable, and maintainable code across data pipelines, APIs, and data platform services.Collaborating with senior engineers, analysts, and product stakeholders to translate technical requirements into working solutions.Developing and supporting APIs, batch and real-time data flows, ensuring reliability and performance in 24x7 environments.Contributing to data modeling, transformation logic, and system design decisions in support of reporting, analytics, and data delivery needs.Participating in the end-to-end software development lifecycle - including planning, testing, deployment, and operations.Taking ownership of features and components, and seeing them through from design to deployment.Documenting technical decisions, workflows, and runbooks to support long-term maintainability and clarity for peers.Practicing responsible data governance, ensuring data quality, privacy, and lineage are considered in all development.Continuously learning and growing through code reviews, pairing, and technical mentorship.Requirements2-4 years of development experience, with production systems in cloud environments.Proficient in Python and/or Golang, and SQL for data processing, transformation, and orchestration tasks.Experience with at least one modern cloud platform (e.g., GCP, AWS, or Azure).Experience developing REST or GraphQL APIs and internal data access layers.Experience building and maintaining ETL/ELT pipelines or API-driven data services.Experience with source control (e.g., Git), automated testing, and CI/CD practices.Exposure to orchestration tooling such as n8n, Cloud scheduler, Airflow, Step Functions, or similar.Understanding of data modeling concepts and cloud warehousing (e.g., Databricks, BigQuery, Snowflake or other).Familiarity with Kafka, Pub/Sub, or other event-based systems.Awareness of data quality, observability, and governance principles in engineering contexts.Strong written and verbal communication skills, with an ability to share context with both technical peers and cross-functional partners.Experience working with containerized environments (e.g., Docker, Kubernetes).Exposure to infrastructure-as-code, especially for deploying and managing data workflows.Hands-on use of BI tools like Looker or Tableau.

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