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

Description :

Experience : 3+ Years

Job Type : Full-time

Location : Sion, Mumbai (On-site)

Also Apply at : https://wohlig.keka.com/careers/jobdetails/122580

The Opportunity :

We are a global technology consultancy driving large-scale digital transformations for the Fortune 500. As a strategic partner to Google, we help enterprise clients navigate complex data landscapes migrating legacy systems to the cloud, optimizing costs, and turning raw data into executive-level insights.

We are seeking a Data Analyst who acts less like a technician and more like a Data Consultant. You will blend deep technical expertise in SQL and ETL with the soft skills required to tell compelling data stories to non-technical stakeholders.

What You Will Do :

- Strategic Cloud Data Architecture : Lead high-impact data migration projects. You will assess a client's legacy infrastructure and design the logic to move it to the cloud efficiently (focusing on scalability and security).

- Cost and Performance Optimization : Audit and optimize cloud data warehouses (e.g., BigQuery, Snowflake, Redshift). You will use logical reasoning to hunt down inefficiencies, optimize queries, and restructure data models to save clients significant operational costs.

- End-to-End Data Pipelines (ETL/ELT) : Build and maintain robust data pipelines. Whether its streaming or batch processing, you will ensure data flows seamlessly from source to dashboard using modern frameworks.

- Data Storytelling & Visualization : This is critical. You will build dashboards (Looker, Tableau, PowerBI) that don't just show numbers but answer business questions. You must be able to present these findings to C-suite clients with clarity and confidence.

- Advanced Analytics : Apply statistical rigor and logical deduction to solve unstructured business problems (e.g., Why is our user retention dropping?).

What We Are Looking For :

1. Core Competencies :

- Logical Reasoning : You possess a deductive mindset. You can break down ambiguous client problems into solvable technical components without needing hand-holding.

- Advanced SQL Mastery : You are fluent in complex SQL (Window functions, CTEs, stored procedures) and understand how to write query-efficient code for massive datasets.

- Communication Skills : You are an articulate storyteller who can bridge the gap between engineering jargon and business value.

2. Technical Experience :

- Cloud Proficiency : 3+ years of experience working within a major public cloud ecosystem (GCP, AWS, or Azure). Note : While we primarily use Google Cloud (BigQuery, Looker), we value strong architectural fundamentals over specific tool knowledge.

- Data Engineering & ETL : Experience with big data processing tools (e.g., Spark, Apache Beam, Databricks, or cloud-native equivalents).

- Visualization : Proven mastery of at least one enterprise BI tool (Looker, Tableau, PowerBI, Qlik).

Why Join us ?

- Cross-Cloud Exposure : While our current focus is GCP, your foundational skills will be challenged and expanded across various tech stacks.

- Client Impact : You aren't just writing code in a back room; you are the face of our data capability, directly advising clients on how to run their businesses better.

- Growth : We offer a structured career path with sponsorship for cloud certifications (Google Professional Data Engineer, etc.).

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.

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