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Senior Data Engineer

at Anblicks

Hyderabad, India Senior Posted 2026-04-07

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About this role

Job Role: Senior Data Engineer- Implementation & Modernization Location: Hyderabad Experience: 5+ Years Job Role Summary The Data Engineer is responsible for building and optimizing high-performance, large-scaled data solutions on modern cloud platforms. This role focuses on developing Senior Data Engineer- Implementation & Modernization Job Role Summary The Data Engineer is responsible for building and optimizing high-performance, large-scaled data solutions on modern cloud platforms. This role focuses on developing data engineering pipelines, working closely with the Cloud Solution Architects who defines overall architectural design. The Data Engineer is expected to deeply understand approved solution designs, data architectures, and modeling patterns to translate them into efficient and secure data pipelines. The ideal candidate brings strong SQL and Python skills, strong collaboration skills, and must be able to integrate solutions with a variety of technologies. The data engineer should be self-driven, able to work with minimum supervision and have extensive experience in Data Modeling, Data Warehousing, and ETL processing in a cloud environment. Duties & Responsibilities Implement high-performing, scalable, data ingestion, transformation, and curation pipelines on cloud platforms, aligned to approved architectural designs and standards Apply best practices in data modeling, data structures, and curated data layers to support business use cases Partner with Cloud Solution Architects to understand solution designs and ensure accurate, efficient implementation, ensuring that all approved development and deployment procedures are followed. Lead code review sessions, providing code assessment Automate data workflows and pipeline operations using orchestration and scheduling tools Monitor pipeline health, proactively identify issues, and troubleshoot data quality or performance problems Optimize data processing workloads for performance, reliability, and cost efficiency Qualifications Required Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent professional experience 5+ years of hand-on data engineering experience in cloud environments Advanced SQL expertise and strong Python programming skills Extensive hands-on experience developing end-to-end ELT/ETL pipelines Demonstrated experience developing high-performance, large scale systems Proven experiences in Snowflake and Databricks Strong experience with data pipeline workflow automation and orchestration frameworks (Preferred: Dagster, DBT) Experience working in controlled development, testing and production environments Familiarity with Git-based version control and CI/CD practices Application of Relational Database Principles and Advanced Features Excellent written and verbal communication skills Strong problem-solving skills and ability to debug complex systems Ability to work independently while collaborating across cross-functional teams Experience using Waterfall and Agile-based methodologies within a software development function Preferred qualifications Cloud certifications in AWS, GCP, Azure, Snowflake, or Databricks Industry expertise in marketing environments and related use cases Experience implementing medallion or layered data architectures Familiarity with observability frameworks and data reliability engineering

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