Sr Cloud Data Engineer
Role Overview
The Senior Data Engineer designs, builds, and optimizes scalable data pipelines, integration solutions, and cloud data platforms.
The platforms support enterprise analytics, reporting, and AI/ML initiatives; the role collaborates with architects, analysts, and business stakeholders.
Key Skills for This Role
Full Job Posting
Job information
Job type is listed as full time.
The posting lists 7–10 years of work experience and IT Services industry.
The job information lists Bengaluru, Karnataka, India.
About BLACKBUCK iNSIGHTS
BLACKBUCK iNSIGHTS is a data engineering consulting firm providing data integration, modernization, migration, architecture, platform support, and application services.
Role overview
The Senior Data Engineer designs, builds, and optimizes scalable data pipelines, integration solutions, and cloud data platforms.
The platforms support enterprise analytics, reporting, and AI/ML initiatives; the role collaborates with architects, analysts, and business stakeholders.
Data engineering and operations
- Design, develop, and maintain scalable pipelines, reusable frameworks, and integrations for structured and unstructured data.
- Build and optimize ETL/ELT processes and support cloud data platforms.
- Manage batch and real-time ingestion, pipeline monitoring, optimization, troubleshooting, and workflow automation.
- Ensure reliable, timely data delivery to downstream consumers.
Quality, governance, and Meridian
- Implement validation, reconciliation, and data quality controls; support governance, metadata, lineage, observability, and organizational standards.
- Support Meridian solution implementation and enhancement, including integrations, testing, deployment, and operational support.
- Translate stakeholder business requirements into technical solutions.
Technical leadership
- Provide technical guidance and mentorship to junior and mid-level engineers.
- Participate in architecture reviews, design sessions, and code reviews; promote engineering best practices and continuous improvement.
- Document technical designs, standards, and operational procedures.
Required qualifications
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, and at least 5 years of Data Engineering or related experience.
- Experience designing enterprise pipelines and integrations; expertise in SQL and one or more of Python, Scala, or Java.
- Experience with ETL/ELT, data warehousing, data lakes, and cloud platforms such as Azure, AWS, or Google Cloud.
- Knowledge of Airflow, Azure Data Factory, or similar orchestration tools, plus data quality, governance, and monitoring concepts.
- Experience troubleshooting and optimizing large-scale data processing solutions.
Preferred qualifications
- Meridian implementation or support experience is preferred.
- Experience with Databricks, Snowflake, Azure Synapse, Microsoft Fabric, or similar platforms is preferred.
- Streaming technology, DevOps, CI/CD, Infrastructure as Code, automated testing, AI/ML pipeline, and feature engineering experience are preferred.
- Relevant cloud, data engineering, or platform certifications are preferred.
Success measures
Success includes reliable and scalable pipelines, improved data quality, timely delivery, and successful Meridian initiatives.
Additional measures include increased automation, operational efficiency, platform stability, and high-quality documentation.
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