Senior Data Solutions Architect

12 hours ago

Delhi, Delhi, India beBeeData Full time ₹ 20,00,000 - ₹ 25,00,000
Job Title: Senior Data Solutions Architect

This role is open to highly motivated professionals who wish to lead in the field of data engineering and work as part of a team that builds scalable data pipelines, architectures, and solutions.

Key Responsibilities:

  • Lead and mentor a team of data engineers in designing, developing, and maintaining large-scale data systems.
  • Architect, build, and optimize ETL workflows using Python, PySpark, and SQL.
  • Collaborate with cross-functional teams including data scientists, analysts, and business stakeholders to understand data requirements and deliver reliable solutions.
  • Implement and manage data integration from multiple structured and unstructured sources.
  • Design and maintain data lake/data warehouse solutions on AWS (S3, Glue, Redshift, EMR, Lambda) or Azure (Data Lake, Synapse, Databricks, Data Factory).
  • Ensure data quality, security, and compliance with best practices.
  • Optimize performance of large-scale data processing systems and pipelines.
  • Drive automation, CI/CD practices, and infrastructure-as-code for data platforms.
  • Provide technical leadership in solution design, code reviews, and architecture decisions.

Required Skills & Qualifications:

  • Strong proficiency in Python, PySpark, and SQL.
  • Proven experience in ETL design and development.
  • Hands-on expertise in big data frameworks (Spark, Hadoop ecosystem).
  • Deep understanding of cloud platforms - AWS (Glue, EMR, Redshift, S3, Lambda) or Azure (Data Factory, Synapse, Databricks, Data Lake).
  • Experience with data modeling, data warehousing, and performance optimization.
  • Strong knowledge of version control (Git), CI/CD pipelines, and DevOps practices.
  • Excellent problem-solving and analytical skills.
  • Strong communication and leadership skills with experience leading teams/projects.

Nice to Have:

  • Experience with streaming platforms (Kafka, Kinesis, Event Hub).
  • Knowledge of containerization & orchestration (Docker, Kubernetes).
  • Exposure to machine learning pipelines or MLOps.
  • Familiarity with data governance and security frameworks.

Bonus Points:

  • Technical certifications in data engineering, cloud computing, or related fields.
  • Contributions to open-source projects or publications in reputable journals.

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