5+ Data architecture Jobs in Mumbai | Data architecture Job openings in Mumbai

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:

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

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.

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.

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.

Role Type: Technical Leadership | Architecture | Client-Facing

Role Overview

We are seeking a Tech Lead – Data Platform who thinks platform-first, not tool-first. This role sits at the intersection of architecture, delivery, and business impact—owning the design of modern data platforms while guiding teams, influencing stakeholders, and shaping scalable, commercially viable solutions.

You will work closely with engineering teams, business leaders, and senior executives to translate data strategy into resilient, cost-effective, and future-ready platforms.

Key Responsibilities

Data Platform Leadership

• Design and lead modern data platforms leveraging lakehouse, streaming, and governance-first architectures
• Drive platform decisions with a focus on scalability, reliability, security, and cost optimization
• Ensure data platforms are built for analytics, operational use cases, and AI readiness

Solution Architecture & Pre-Sales

• Partner with sales and leadership teams during pre-sales, discovery, and solution shaping
• Whiteboard architectures, qualify opportunities, and recommend right-fit platform approaches
• Convert ambiguous business problems into structured technical solutions and delivery plans

Business Value & Commercial Impact

• Translate platform capabilities into clear business outcomes—revenue growth, operational efficiency, risk reduction, and ROI
• Support land-and-expand strategies, helping grow initial engagements into multi-phase programs
• Balance technical ambition with commercial pragmatism

Cloud & Technology Expertise

• Architect solutions across AWS, Azure, or GCP data ecosystems
• Make informed trade-offs around storage, compute, streaming, orchestration, and governance tooling
• Maintain strong cost-awareness and scaling discipline in platform design

Platform & Practice Building

• Create reference architectures, accelerators, and reusable assets to improve delivery velocity
• Contribute to internal best practices, standards, and technical playbooks
• Support the evolution of data platform offerings and service lines

Executive & Stakeholder Engagement

• Act as a credible technology partner to CIOs, CDOs, and CTOs
• Communicate complex technical concepts clearly to non-technical stakeholders
• Operate confidently in regulated environments (financial services, healthcare, etc.)

Technical Leadership & Mentorship

• Stay hands-on enough to review designs, challenge assumptions, and guide implementation
• Mentor engineers and senior developers; influence hiring and upskilling decisions
• Foster a culture of quality, ownership, and continuous learning

GenAI & Emerging Tech

• Understand and position GenAI and AI/ML as outcomes enabled by strong data platforms
• Avoid AI-first hype; ensure foundational data readiness before advanced use cases

Required Skills & Experience

• 5–9 years of experience in data engineering, data platform architecture, or analytics platforms
• Strong understanding of lakehouse, streaming, metadata, governance, and data security concepts
• Hands-on experience with cloud data stacks on AWS
• Experience working with stakeholders across engineering, business, and leadership
• Exposure to client-facing roles, consulting, or solution design is a strong plus
• Ability to balance technical depth with business and commercial thinking

What We’re Looking For

• Platform thinker, not a tool specialist
• Comfortable with ambiguity and ownership
• Strong communicator with executive presence
• Builder mindset with long-term vision
• Pragmatic, outcome-driven, and commercially aware

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