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ROLES AND RESPONSIBILITIES:

You will be responsible for architecting, implementing, and optimizing Dremio-based data Lakehouse environments integrated with cloud storage, BI, and data engineering ecosystems. The role requires a strong balance of architecture design, data modeling, query optimization, and governance enablement in large-scale analytical environments.

• Design and implement Dremio lakehouse architecture on cloud (AWS/Azure/Snowflake/Databricks ecosystem).
• Define data ingestion, curation, and semantic modeling strategies to support analytics and AI workloads.
• Optimize Dremio reflections, caching, and query performance for diverse data consumption patterns.
• Collaborate with data engineering teams to integrate data sources via APIs, JDBC, Delta/Parquet, and object storage layers (S3/ADLS).
• Establish best practices for data security, lineage, and access control aligned with enterprise governance policies.
• Support self-service analytics by enabling governed data products and semantic layers.
• Develop reusable design patterns, documentation, and standards for Dremio deployment, monitoring, and scaling.
• Work closely with BI and data science teams to ensure fast, reliable, and well-modeled access to enterprise data.

IDEAL CANDIDATE:

• Bachelor’s or Master’s in Computer Science, Information Systems, or related field.
• 5+ years in data architecture and engineering, with 3+ years in Dremio or modern lakehouse platforms.
• Strong expertise in SQL optimization, data modeling, and performance tuning within Dremio or similar query engines (Presto, Trino, Athena).
• Hands-on experience with cloud storage (S3, ADLS, GCS), Parquet/Delta/Iceberg formats, and distributed query planning.
• Knowledge of data integration tools and pipelines (Airflow, DBT, Kafka, Spark, etc.).
• Familiarity with enterprise data governance, metadata management, and role-based access control (RBAC).
• Excellent problem-solving, documentation, and stakeholder communication skills.

PREFERRED:

• Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) and data catalogs (Collibra, Alation, Purview).
• Exposure to Snowflake, Databricks, or BigQuery environments.
• Experience in high-tech, manufacturing, or enterprise data modernization programs.

About The Role

• As a Data Platform Lead, you will utilize your strong technical background and hands-on development skills to design, develop, and maintain data platforms.
• Leading a team of skilled data engineers, you will create scalable and robust data solutions that enhance business intelligence and decision-making.
• You will ensure the reliability, efficiency, and scalability of data systems while mentoring your team to achieve excellence.
• Collaborating closely with our client’s CXO-level stakeholders, you will oversee pre-sales activities, solution architecture, and project execution.
• Your ability to stay ahead of industry trends and integrate the latest technologies will be crucial in maintaining our competitive edge.

Key Responsibilities

• Client-Centric Approach: Understand client requirements deeply and translate them into robust technical specifications, ensuring solutions meet their business needs.
• Architect for Success: Design scalable, reliable, and high-performance systems that exceed client expectations and drive business success.
• Lead with Innovation: Provide technical guidance, support, and mentorship to the development team, driving the adoption of cutting-edge technologies and best practices.
• Champion Best Practices: Ensure excellence in software development and IT service delivery, constantly assessing and evaluating new technologies, tools, and platforms for project suitability.
• Be the Go-To Expert: Serve as the primary point of contact for clients throughout the project lifecycle, ensuring clear communication and high levels of satisfaction.
• Build Strong Relationships: Cultivate and manage relationships with CxO/VP level stakeholders, positioning yourself as a trusted advisor.
• Deliver Excellence: Manage end-to-end delivery of multiple projects, ensuring timely and high-quality outcomes that align with business goals.
• Report with Clarity: Prepare and present regular project status reports to stakeholders, ensuring transparency and alignment.
• Collaborate Seamlessly: Coordinate with cross-functional teams to ensure smooth and efficient project execution, breaking down silos and fostering collaboration.
• Grow the Team: Provide timely and constructive feedback to support the professional growth of team members, creating a high-performance culture.

Qualifications

• Master’s (M. Tech., M.S.) in Computer Science or equivalent from reputed institutes like IIT, NIT preferred
• Overall 6–8 years of experience with minimum 2 years of relevant experience and a strong technical background
• Experience working in mid size IT Services company is preferred

Preferred Certification

• AWS Certified Data Analytics Specialty
• AWS Solution Architect Professional
• Azure Data Engineer + Solution Architect
• Databricks Certified Data Engineer / ML Professional

Technical Expertise

• Advanced knowledge of distributed architectures and data modeling practices.
• Extensive experience with Data Lakehouse systems like Databricks and data warehousing solutions such as Redshift and Snowflake.
• Hands-on experience with data technologies such as Apache Spark, SQL, Airflow, Kafka, Jenkins, Hadoop, Flink, Hive, Pig, HBase, Presto, and Cassandra.
• Knowledge in BI tools including PowerBi, Tableau, Quicksight and open source equivalent like Superset and Metabase is good to have.
• Strong knowledge of data storage formats including Iceberg, Hudi, and Delta.
• Proficient programming skills in Python, Scala, Go, or Java.
• Ability to architect end-to-end solutions from data ingestion to insights, including designing data integrations using ETL and other data integration patterns.
• Experience working with multi-cloud environments, particularly AWS and Azure.
• Excellent teamwork and communication skills, with the ability to thrive in a fast-paced, agile environment.

Review Criteria

• Strong Dremio / Lakehouse Data Architect profile
• 5+ years of experience in Data Architecture / Data Engineering, with minimum 3+ years hands-on in Dremio
• Strong expertise in SQL optimization, data modeling, query performance tuning, and designing analytical schemas for large-scale systems
• Deep experience with cloud object storage (S3 / ADLS / GCS) and file formats such as Parquet, Delta, Iceberg along with distributed query planning concepts
• Hands-on experience integrating data via APIs, JDBC, Delta/Parquet, object storage, and coordinating with data engineering pipelines (Airflow, DBT, Kafka, Spark, etc.)
• Proven experience designing and implementing lakehouse architecture including ingestion, curation, semantic modeling, reflections/caching optimization, and enabling governed analytics
• Strong understanding of data governance, lineage, RBAC-based access control, and enterprise security best practices
• Excellent communication skills with ability to work closely with BI, data science, and engineering teams; strong documentation discipline
• Candidates must come from enterprise data modernization, cloud-native, or analytics-driven companies

Preferred

• Preferred (Nice-to-have) – Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) or data catalogs (Collibra, Alation, Purview); familiarity with Snowflake, Databricks, or BigQuery environments

Job Specific Criteria

• CV Attachment is mandatory
• How many years of experience you have with Dremio?
• Which is your preferred job location (Mumbai / Bengaluru / Hyderabad / Gurgaon)?
• Are you okay with 3 Days WFO?
• Virtual Interview requires video to be on, are you okay with it?

Role & Responsibilities

You will be responsible for architecting, implementing, and optimizing Dremio-based data lakehouse environments integrated with cloud storage, BI, and data engineering ecosystems. The role requires a strong balance of architecture design, data modeling, query optimization, and governance enablement in large-scale analytical environments.

• Design and implement Dremio lakehouse architecture on cloud (AWS/Azure/Snowflake/Databricks ecosystem).
• Define data ingestion, curation, and semantic modeling strategies to support analytics and AI workloads.
• Optimize Dremio reflections, caching, and query performance for diverse data consumption patterns.
• Collaborate with data engineering teams to integrate data sources via APIs, JDBC, Delta/Parquet, and object storage layers (S3/ADLS).
• Establish best practices for data security, lineage, and access control aligned with enterprise governance policies.
• Support self-service analytics by enabling governed data products and semantic layers.
• Develop reusable design patterns, documentation, and standards for Dremio deployment, monitoring, and scaling.
• Work closely with BI and data science teams to ensure fast, reliable, and well-modeled access to enterprise data.

Ideal Candidate

• Bachelor’s or master’s in computer science, Information Systems, or related field.
• 5+ years in data architecture and engineering, with 3+ years in Dremio or modern lakehouse platforms.
• Strong expertise in SQL optimization, data modeling, and performance tuning within Dremio or similar query engines (Presto, Trino, Athena).
• Hands-on experience with cloud storage (S3, ADLS, GCS), Parquet/Delta/Iceberg formats, and distributed query planning.
• Knowledge of data integration tools and pipelines (Airflow, DBT, Kafka, Spark, etc.).
• Familiarity with enterprise data governance, metadata management, and role-based access control (RBAC).
• Excellent problem-solving, documentation, and stakeholder communication skills.

Role Overview:

We are seeking a talented and experienced Data Architect with strong data visualization capabilities to join our dynamic team in Mumbai. As a Data Architect, you will be responsible for designing, building, and managing our data infrastructure, ensuring its reliability, scalability, and performance. You will also play a crucial role in transforming complex data into insightful visualizations that drive business decisions. This role requires a deep understanding of data modeling, database technologies (particularly Oracle Cloud), data warehousing principles, and proficiency in data manipulation and visualization tools, including Python and SQL.

Responsibilities:

• Design and implement robust and scalable data architectures, including data warehouses, data lakes, and operational data stores, primarily leveraging Oracle Cloud services.
• Develop and maintain data models (conceptual, logical, and physical) that align with business requirements and ensure data integrity and consistency.
• Define data governance policies and procedures to ensure data quality, security, and compliance.
• Collaborate with data engineers to build and optimize ETL/ELT pipelines for efficient data ingestion, transformation, and loading.
• Develop and execute data migration strategies to Oracle Cloud.
• Utilize strong SQL skills to query, manipulate, and analyze large datasets from various sources.
• Leverage Python and relevant libraries (e.g., Pandas, NumPy) for data cleaning, transformation, and analysis.
• Design and develop interactive and insightful data visualizations using tools like [Specify Visualization Tools - e.g., Tableau, Power BI, Matplotlib, Seaborn, Plotly] to communicate data-driven insights to both technical and non-technical stakeholders.
• Work closely with business analysts and stakeholders to understand their data needs and translate them into effective data models and visualizations.
• Ensure the performance and reliability of data visualization dashboards and reports.
• Stay up-to-date with the latest trends and technologies in data architecture, cloud computing (especially Oracle Cloud), and data visualization.
• Troubleshoot data-related issues and provide timely resolutions.
• Document data architectures, data flows, and data visualization solutions.
• Participate in the evaluation and selection of new data technologies and tools.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, or a related field.
• Proven experience (typically 5+ years) as a Data Architect, Data Modeler, or similar role. 
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• Deep understanding of data warehousing concepts, dimensional modeling (e.g., star schema, snowflake schema), and ETL/ELT processes.
• Extensive experience working with relational databases, particularly Oracle, and proficiency in SQL.
• Hands-on experience with Oracle Cloud data services (e.g., Autonomous Data Warehouse, Object Storage, Data Integration).
• Strong programming skills in Python and experience with data manipulation and analysis libraries (e.g., Pandas, NumPy).
• Demonstrated ability to create compelling and effective data visualizations using industry-standard tools (e.g., Tableau, Power BI, Matplotlib, Seaborn, Plotly).
• Excellent analytical and problem-solving skills with the ability to interpret complex data and translate it into actionable insights. 
• Strong communication and presentation skills, with the ability to effectively communicate technical concepts to non-technical audiences. 
• Experience with data governance and data quality principles.
• Familiarity with agile development methodologies.
• Ability to work independently and collaboratively within a team environment.
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Application Link- https://forms.gle/km7n2WipJhC2Lj2r5