Data Architect

2 weeks ago

Hyderabad, Telangana, India Covasant Full time ₹ 20,00,000 - ₹ 25,00,000 per year
  • Experience
    : Yrs of experience as a Data Architect in complex, large-scale data environments.
  • SSIS, Databricks Expertise
    : Strong hands-on experience working with SSIS, Databricks, including using Apache Spark for data processing and optimization.
  • ETL Tools
    : Proficient with various ETL tools and frameworks such as Informatica, Talend, or SSIS or DataBricks
  • Big Data Technologies:
    In-depth knowledge of big data processing frameworks like Spark, Flink, Hadoop, Kafka, etc.
  • NoSQL/MongoDB:
    Expertise in working with NoSQL databases, especially MongoDB, for large-scale data storage, retrieval, and optimization.
  • Gen AI/AIML Models :
    Familiarity with data consumption.
  • Programming Skills:
    Proficient in SQL , Python or Java, Power shell for building data pipelines.
  • SQL and NoSQL Proficiency:
    Strong knowledge of SQL and experience working with both relational databases and NoSQL databases like MongoDB.
  • Data Modeling:
    Expertise in designing and implementing data models, including OLAP, OLTP, dimensional, and document-based models (NoSQL
  • Data Reporting:
    Experience in integrating with Reporting platforms like Tableau, Qlik, etc
  • Data warehousing:
    Data warehousing is a key part of ETL process, as it stores data from multiple sources in an organized manner and will be needed to build a repeatable ETL workflow to support many different data sources. Experience in building Datawarehouse,
    Datalakes in Snowflake.
  • Redesign and refactor legacy custom ETL processes to reusable ETL workflows that can ingest diverse data sources to normalize data to standard JSON / XML output.
  • Data Governance:
    Knowledge of data governance, security standards, and best practices for managing sensitive data.
  • Version Control:
    Experience with Git or other version control systems for code management.
  • Certification:
    Databricks certification, MongoDB certification, Snowflake SnowPro certification, or other relevant certifications in data engineering, cloud platforms (AWS, Azure or GCP or TKGI), or big data technologies.
  • Soft Skills:
    Strong problem-solving skills, excellent communication, and the ability to work in a collaborative team environment.
  • Analytical Mindset:
    Ability to translate business requirements into scalable, efficient, and reliable ETL solutions.
  • Knowledge on AI/ML/GEN AI is desirable

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