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Brillio

Databricks Data Specialist - R01569707

Bengaluru · Mid Level

Older listing - lower visibility likelyVerified listingPosted 56d ago

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Your match scoreCalculated · locked
86Overall
64Skills
97Experience

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Skills required

21 listed
Azure Data FactoryData LayersAccess ControlsApache SparkAWS GlueAWS LambdaApache AirflowApache Kafka+13 more
Azure Data FactoryData LayersAccess ControlsApache SparkAWS Glue

You almost certainly match several of these already. Unlock your skill map to see the matches, the gaps, and what to fix first.

Job description

Data Specialist


Primary Skills

Databricks Engineer

Role Overview

We are seeking a highly skilled Databricks Engineer to design, develop, and optimize scalable data engineering and analytics solutions on the Databricks Lakehouse Platform. The ideal candidate will possess strong expertise in Databricks, PySpark, and SQL, with hands-on experience building batch and real-time data pipelines, implementing Lakehouse architectures, and ensuring data governance and performance optimization.

Key Responsibilities

  • Design, develop, and maintain end-to-end data pipelines using Databricks and PySpark.
  • Build and implement Lakehouse architectures utilizing Bronze, Silver, and Gold data layers.
  • Develop and manage Delta Lake solutions with ACID transactions, schema enforcement, and data reliability features.
  • Create, monitor, and optimize Delta Live Tables (DLT) pipelines.
  • Implement scalable and efficient data ingestion processes using Auto Loader.
  • Develop and manage real-time data processing solutions using Structured Streaming.
  • Orchestrate, schedule, and monitor data workflows using Databricks Workflows.
  • Design and implement Lakehouse data models to support reporting, analytics, and business intelligence requirements.
  • Establish and enforce data governance, security, and access controls using Unity Catalog.
  • Optimize Spark jobs, SQL queries, and overall platform performance to ensure efficiency and scalability.
  • Collaborate with cross-functional teams, including data analysts, architects, and business stakeholders, to deliver high-quality data solutions.

    • Required Skills (Must Have)

  • Databricks Platform
  • Delta Lake
  • Delta Live Tables (DLT)
  • Unity Catalog
  • Databricks Workflows
  • PySpark and Apache Spark
  • Structured Streaming
  • Auto Loader
  • SQL
  • Lakehouse Data Modeling
  • Strong understanding of data engineering best practices and scalable data architectures

    • Preferred Skills (Good to Have)

    Azure Ecosystem

  • Azure Data Factory (ADF)
  • Azure Synapse Analytics
  • Microsoft Purview
  • Microsoft Fabric

    • AWS Ecosystem

  • AWS Glue
  • AWS Lambda
  • AWS Step Functions

    • Data Engineering & Integration

  • Apache Airflow
  • DBT
  • Fivetran
  • Informatica

    • Streaming & Analytics

  • Apache Kafka
  • Power BI

    • Data Governance

  • Collibra
  • Alation

    • GCP

  • BigQuery

    • Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Information Technology, or a related discipline.
  • Proven experience in designing and implementing cloud-based data engineering solutions and scalable data pipelines.
  • Strong analytical, troubleshooting, and problem-solving capabilities.
  • Experience working in agile and collaborative environments.
  • Excellent communication and stakeholder management skills.

    • Preferred Candidate Profile

  • Hands-on experience with modern Lakehouse architectures and enterprise-scale data platforms.
  • Strong understanding of data governance, security, and compliance frameworks.
  • Experience delivering both batch and real-time data processing solutions.
  • Ability to work independently while collaborating effectively across global teams.

    • Key Technologies

    Databricks | PySpark | Apache Spark | Delta Lake | Delta Live Tables (DLT) | Unity Catalog | Structured Streaming | Auto Loader | SQL | Lakehouse Architecture | Azure | AWS | Airflow | Kafka | Power BI



    Specialization
  • Databricks Engineering: Lead Data Engineer


    • Job requirements

    Databricks Engineer

    Role Overview

    We are seeking a highly skilled Databricks Engineer to design, develop, and optimize scalable data engineering and analytics solutions on the Databricks Lakehouse Platform. The ideal candidate will possess strong expertise in Databricks, PySpark, and SQL, with hands-on experience building batch and real-time data pipelines, implementing Lakehouse architectures, and ensuring data governance and performance optimization.

    Key Responsibilities

  • Design, develop, and maintain end-to-end data pipelines using Databricks and PySpark.
  • Build and implement Lakehouse architectures utilizing Bronze, Silver, and Gold data layers.
  • Develop and manage Delta Lake solutions with ACID transactions, schema enforcement, and data reliability features.
  • Create, monitor, and optimize Delta Live Tables (DLT) pipelines.
  • Implement scalable and efficient data ingestion processes using Auto Loader.
  • Develop and manage real-time data processing solutions using Structured Streaming.
  • Orchestrate, schedule, and monitor data workflows using Databricks Workflows.
  • Design and implement Lakehouse data models to support reporting, analytics, and business intelligence requirements.
  • Establish and enforce data governance, security, and access controls using Unity Catalog.
  • Optimize Spark jobs, SQL queries, and overall platform performance to ensure efficiency and scalability.
  • Collaborate with cross-functional teams, including data analysts, architects, and business stakeholders, to deliver high-quality data solutions.

    • Required Skills (Must Have)

  • Databricks Platform
  • Delta Lake
  • Delta Live Tables (DLT)
  • Unity Catalog
  • Databricks Workflows
  • PySpark and Apache Spark
  • Structured Streaming
  • Auto Loader
  • SQL
  • Lakehouse Data Modeling
  • Strong understanding of data engineering best practices and scalable data architectures

    • Preferred Skills (Good to Have)

    Azure Ecosystem

  • Azure Data Factory (ADF)
  • Azure Synapse Analytics
  • Microsoft Purview
  • Microsoft Fabric

    • AWS Ecosystem

  • AWS Glue
  • AWS Lambda
  • AWS Step Functions

    • Data Engineering & Integration

  • Apache Airflow
  • DBT
  • Fivetran
  • Informatica

    • Streaming & Analytics

  • Apache Kafka
  • Power BI

    • Data Governance

  • Collibra
  • Alation

    • GCP

  • BigQuery

    • Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Information Technology, or a related discipline.
  • Proven experience in designing and implementing cloud-based data engineering solutions and scalable data pipelines.
  • Strong analytical, troubleshooting, and problem-solving capabilities.
  • Experience working in agile and collaborative environments.
  • Excellent communication and stakeholder management skills.

    • Preferred Candidate Profile

  • Hands-on experience with modern Lakehouse architectures and enterprise-scale data platforms.
  • Strong understanding of data governance, security, and compliance frameworks.
  • Experience delivering both batch and real-time data processing solutions.
  • Ability to work independently while collaborating effectively across global teams.

    • Key Technologies

    Databricks | PySpark | Apache Spark | Delta Lake | Delta Live Tables (DLT) | Unity Catalog | Structured Streaming | Auto Loader | SQL | Lakehouse Architecture | Azure | AWS | Airflow | Kafka | Power BI

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    Two ways in

    Applicants who checked fit first are 3.1× more likely to hear back

    Your match scoreCalculated · locked
    86Overall
    64Skills
    97Experience

    Your score for this role already exists

    ASAI compared this JD against 41 signals - skills, seniority, domain, stack overlap etc. Add a resume and it unlocks in about 30 seconds.

    No credit card · 1 tap with Google

    Free · no signup

    Get tomorrow's jobs before you have to search

    Daily job drops, skill trends and free resources - posted straight to the group. Leave any time.

    Join WhatsAppJoin Telegram

    No spam. Just jobs and resources.

    Why people use ASAI

    Someone shared one job with you. ASAI keeps finding the rest.

    • Scored, not searched. Every role ranked against your actual profile.

    • Alerts as often as hourly. Reach new roles while the pile is still small.

    • Skill gaps, spelled out. See exactly which requirements you don't meet yet.

    • Verified jobs, only. Say no to ghost jobs. Your time deserves respect.

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