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Data Consultant II

Job Description - Data Consultant II

We are seeking an experienced Data Consultant to design, develop, and optimize enterprise -grade data platforms across modern cloud ecosystems. The ideal candidate will have strong expertise in platforms such as Databricks, Snowflake, and Amazon Redshift, along with hands -on experience in scalable data engineering, cloud -native architectures, and performance optimization.

The candidate will play a key role in solution implementation, stakeholder communication, architecture design, mentoring junior engineers, and driving best practices across data platforms.

Key Responsibilities

  • Design scalable, secure, and high -performance data architectures using Databricks, Snowflake, and Redshift.
  • Develop and optimize ETL/ELT pipelines for batch and real -time processing.
  • Build and tune Spark workloads and SQL -based transformations for large -scale data processing.
  • Lead migration and modernization initiatives from traditional data warehouses to cloud -native data platforms.
  • Implement Delta Lake best practices including partitioning, Z -ordering, optimization, and data lifecycle management.
  • Design robust data models including Star Schema, Snowflake Schema, and Data Vault methodologies.
  • Ensure governance, security, and access controls using frameworks such as Unity Catalog, RBAC, and cloud -native security services.
  • Collaborate with business stakeholders, architects, and engineering teams to translate business requirements into scalable technical solutions.
  • Implement CI/CD pipelines and DevOps best practices for data engineering deployments.
  • Work with orchestration and workflow management tools such as Airflow, ADF, or similar platforms.
  • Mentor Associate Consultants and Engineers through technical guidance, code reviews, and best practices.
  • Monitor and optimize platform performance, reliability, and cost efficiency.



  • Requirements

    • Bachelor’s degree in Computer Science, Information Technology, or a related field.
    • 4–6 years of experience in Data Engineering or Data Consulting.
    • Strong hands -on expertise in at least one modern data platform: Databricks, Snowflake, or Amazon Redshift.
    • Strong experience with Apache Spark, PySpark, SQL, and Python.
    • Deep understanding of performance tuning and optimization techniques across distributed data systems.
    • Strong knowledge of cloud platforms such as AWS, Azure, or GCP.
    • Experience building enterprise -scale ETL/ELT pipelines and data integration frameworks.
    • Hands -on experience with orchestration tools such as Airflow, Azure Data Factory (ADF), or similar.
    • Strong understanding of data warehousing concepts and dimensional data modeling.
    • Knowledge of data governance, security, and compliance frameworks.
    • Experience with Git, CI/CD pipelines, and DevOps practices in data engineering environments.

    Good to Have

    • Experience with real -time or streaming data processing.
    • Exposure to Delta Live Tables (DLT) and Databricks Lakehouse architecture.
    • Experience working with dbt or modern transformation frameworks.
    • Databricks, Snowflake, or AWS certifications.
    • Exposure to data quality, observability, and monitoring tools.

    Signs you may be a great fit

    • Impact: Play a pivotal role in shaping a rapidly growing venture studio.

    • Culture: Thrive in a collaborative, innovative environment that values creativity and ownership.

    • Growth: Access professional development opportunities and mentorship.

    • Benefits: Competitive salary, health/wellness packages, and flexible work options.



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