7+ Data architecture Jobs in Hyderabad | Data architecture Job openings in Hyderabad

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.

JOB DETAILS:

* Job Title: Lead II - Software Engineering - AWS, Apache Spark (PySpark/Scala), Apache Kafka

* Industry: Global digital transformation solutions provider

* Salary: Best in Industry

* Experience: 5-8 years

* Location: Hyderabad

Job Summary

We are seeking a skilled Data Engineer to design, build, and optimize scalable data pipelines and cloud-based data platforms. The role involves working with large-scale batch and real-time data processing systems, collaborating with cross-functional teams, and ensuring data reliability, security, and performance across the data lifecycle.

Key Responsibilities

ETL Pipeline Development & Optimization

• Design, develop, and maintain complex end-to-end ETL pipelines for large-scale data ingestion and processing.
• Optimize data pipelines for performance, scalability, fault tolerance, and reliability.

Big Data Processing

• Develop and optimize batch and real-time data processing solutions using Apache Spark (PySpark/Scala) and Apache Kafka.
• Ensure fault-tolerant, scalable, and high-performance data processing systems.

Cloud Infrastructure Development

• Build and manage scalable, cloud-native data infrastructure on AWS.
• Design resilient and cost-efficient data pipelines adaptable to varying data volume and formats.

Real-Time & Batch Data Integration

• Enable seamless ingestion and processing of real-time streaming and batch data sources (e.g., AWS MSK).
• Ensure consistency, data quality, and a unified view across multiple data sources and formats.

Data Analysis & Insights

• Partner with business teams and data scientists to understand data requirements.
• Perform in-depth data analysis to identify trends, patterns, and anomalies.
• Deliver high-quality datasets and present actionable insights to stakeholders.

CI/CD & Automation

• Implement and maintain CI/CD pipelines using Jenkins or similar tools.
• Automate testing, deployment, and monitoring to ensure smooth production releases.

Data Security & Compliance

• Collaborate with security teams to ensure compliance with organizational and regulatory standards (e.g., GDPR, HIPAA).
• Implement data governance practices ensuring data integrity, security, and traceability.

Troubleshooting & Performance Tuning

• Identify and resolve performance bottlenecks in data pipelines.
• Apply best practices for monitoring, tuning, and optimizing data ingestion and storage.

Collaboration & Cross-Functional Work

• Work closely with engineers, data scientists, product managers, and business stakeholders.
• Participate in agile ceremonies, sprint planning, and architectural discussions.

Skills & Qualifications

Mandatory (Must-Have) Skills

1. AWS Expertise

• Hands-on experience with AWS Big Data services such as EMR, Managed Apache Airflow, Glue, S3, DMS, MSK, and EC2.
• Strong understanding of cloud-native data architectures.

1. Big Data Technologies

• Proficiency in PySpark or Scala Spark and SQL for large-scale data transformation and analysis.
• Experience with Apache Spark and Apache Kafka in production environments.

1. Data Frameworks

• Strong knowledge of Spark DataFrames and Datasets.

1. ETL Pipeline Development

• Proven experience in building scalable and reliable ETL pipelines for both batch and real-time data processing.

1. Database Modeling & Data Warehousing

• Expertise in designing scalable data models for OLAP and OLTP systems.

1. Data Analysis & Insights

• Ability to perform complex data analysis and extract actionable business insights.
• Strong analytical and problem-solving skills with a data-driven mindset.

1. CI/CD & Automation

• Basic to intermediate experience with CI/CD pipelines using Jenkins or similar tools.
• Familiarity with automated testing and deployment workflows.

Good-to-Have (Preferred) Skills

• Knowledge of Java for data processing applications.
• Experience with NoSQL databases (e.g., DynamoDB, Cassandra, MongoDB).
• Familiarity with data governance frameworks and compliance tooling.
• Experience with monitoring and observability tools such as AWS CloudWatch, Splunk, or Dynatrace.
• Exposure to cost optimization strategies for large-scale cloud data platforms.

Skills: big data, scala spark, apache spark, ETL pipeline development

******

Notice period - 0 to 15 days only

Job stability is mandatory

Location: Hyderabad

Note: If a candidate is a short joiner, based in Hyderabad, and fits within the approved budget, we will proceed with an offer

F2F Interview: 14th Feb 2026

3 days in office, Hybrid model.

Job Title: Databricks Architect

Experience Level: Senior (Architect-level)

Role Type: Full-time

Role Overview

We are looking for a highly experienced Databricks Architect to design, migrate, and optimize large-scale data platforms on Databricks. This is a senior-level role requiring strong architectural ownership, hands-on experience with Databricks migrations, and deep expertise in modern data engineering ecosystems.

The ideal candidate has prior experience in data architecture roles before Databricks, and has successfully transitioned data platforms into the Databricks environment while ensuring scalability, performance, and cost efficiency.

Key Responsibilities

• Design and lead end-to-end data architecture solutions using Databricks
• Own and execute data migration strategies into Databricks from legacy or cloud data platforms
• Architect scalable Lakehouse solutions using Delta Lake, Spark, and cloud-native services
• Define best practices for data modeling, ingestion, processing, and governance
• Collaborate with data engineers, analytics teams, and stakeholders to translate business requirements into technical designs
• Optimize performance, reliability, and cost of Databricks workloads
• Ensure data security, compliance, and access controls within Databricks environments
• Review and guide implementation through design reviews and technical governance

Required Skills & Experience

• Several years of experience as a Data Architect / Databricks Architect
• Strong hands-on experience with Databricks (Spark, Delta Lake, Lakehouse architecture)
• Proven track record of migrating data platforms into Databricks
• Solid background in data engineering prior to Databricks adoption
• Deep understanding of distributed systems and big data architectures
• Experience with cloud platforms (AWS / Azure / GCP)
• Strong expertise in ETL/ELT pipelines, data modeling, and performance tuning
• Excellent problem-solving and stakeholder communication skills

Good to Have

• Databricks Certifications (Architect / Data Engineer / Professional level)
• Experience with governance tools (Unity Catalog, data lineage, metadata management)
• Exposure to streaming frameworks and real-time data processing

Ideal Candidate Profile

• Senior architect who has designed and owned Databricks-based solutions
• Comfortable making architectural decisions and guiding teams
• Strong balance of hands-on expertise and high-level system design
• Experience working in complex, enterprise-scale data environments

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.

Lead Software Engineer – FullStack | System & Data Architecture

This is a full-time core team role based in Hyderabad at a funded startup.

At CraftMyPlate, we’re transforming how India orders food for group gatherings — from office teams to family celebrations.

Our platform blends deep operational intelligence, delightful user experiences, and highly scalable systems to make bulk food ordering (10+ people) truly effortless.

We’re backed by leading investors and are entering an exciting scale phase — building the Event OS for India.

What You’ll Own

• Architect and build event-driven, cloud-native systems with clean data foundations, observability, and horizontal scalability at their core.
• Lead backend development using Node.js & TypeScript; contribute to frontend using React + TypeScript and Flutter where needed.
• Design efficient MySQL and Elasticsearch data models and pipelines to power real-time operations and analytics.
• Contribute to data architecture and early machine learning use cases such as pricing, recommendations, and operational forecasts.
• Own infrastructure and deployments on AWS, ensuring reliability, security, and cost efficiency.
• Mentor engineers, drive architecture/code reviews, and set high technical standards for the team.
• Collaborate closely with Product Managers, Founders, Design, and Operations to ship high-impact systems quickly and reliably.

What We’re Looking For

• 6+ years of experience as a Full Stack Engineer, with deep backend expertise.
• Proven track record in system and data architecture, ideally at fast-growing startups or high-scale platforms.
• Strong proficiency in Node.js, TypeScript, React, Flutter, and AWS.
• Expertise in MySQL, Elasticsearch, and distributed system design.
• Experience integrating with ML pipelines is a strong plus.
• Excellent communication, leadership, and problem-solving skills.
• Bachelor’s or Master’s degree in Computer Science or related field.
• A builder’s mindset — thrives in high-ownership, fast-execution environments.

Why CraftMyPlate

• Shape the core architecture of a platform that will scale 10× in the next 12 months.
• Work directly with founders and product leadership on strategic technology initiatives.
• Tackle challenging real-world problems that blend data, systems, and physical operations.
• High autonomy, rapid decision-making, and visible impact.
• Competitive compensation and ESOPs.

Enterprise Data Architect - Dataeconomy (25+ Years Experience)

About Dataeconomy:

Dataeconomy is a rapidly growing company at the forefront of Information Technology. We are driven by data and committed to using it to make better decisions, improve our products, and deliver exceptional value to our customers.

Job Summary:

Dataeconomy seeks a seasoned and strategic Enterprise Data Architect to lead the company's data transformation journey. With 25+ years of experience in data architecture and leadership, you will be pivotal in shaping our data infrastructure, governance, and culture. You will leverage your extensive expertise to build a foundation for future growth and innovation, ensuring our data assets are aligned with business objectives and drive measurable value.

Responsibilities:

Strategic Vision and Leadership:

Lead the creation and execution of a long-term data strategy aligned with the company's overall vision and goals.

Champion a data-driven culture across the organization, fostering cross-functional collaboration and data literacy.

Advise senior leadership on strategic data initiatives and their impact on business performance.

Architecture and Modernization:

Evaluate and modernize the existing data architecture, recommending and implementing innovative solutions.

Design and implement a scalable data lake/warehouse architecture for future growth.

Advocate for and adopt cutting-edge data technologies and best practices.

ETL Tool Experience (8+ years):

Extensive experience in designing, developing, and implementing ETL (Extract, Transform, Load) processes using industry-standard tools such as Informatica PowerCenter, IBM DataStage, Microsoft SSIS, or open-source options like Apache Airflow.

Proven ability to build and maintain complex data pipelines that integrate data from diverse sources, transform it into usable formats, and load it into target systems.

Deep understanding of data quality and cleansing techniques to ensure the accuracy and consistency of data across the organization.

Data Governance and Quality:

Establish and enforce a comprehensive data governance framework ensuring data integrity, consistency, and security.

Develop and implement data quality standards and processes for continuous data improvement.

Oversee the implementation of master data management and data lineage initiatives.

Collaboration and Mentorship:

Mentor and guide data teams, including architects, engineers, and analysts, on data architecture principles and best practices.

Foster a collaborative environment where data insights are readily shared and acted upon across the organization.

Build strong relationships with business stakeholders to understand and translate their data needs into actionable solutions.

Qualifications:

Education: master’s degree in computer science, Information Systems, or related field; Ph.D. preferred.

Experience: 25+ years of experience in data architecture and design, with 10+ years in a leadership role.

Technical Skills:

Deep understanding of TOGAF, AWS, MDM, EDW, Hadoop ecosystem (MapReduce, Hive, HBase, Pig, Flume, Scoop), cloud data platforms (Azure Synapse, Google Big Query), modern data pipelines, streaming analytics, data governance frameworks.

Proficiency in programming languages (Java, Python, SQL), scripting languages (Bash, Python), data modelling tools (ER diagramming software), and BI tools.

Extensive expertise in ETL tools (Informatica PowerCenter, IBM DataStage, Microsoft SSIS, Apache Airflow)

Familiarity with emerging data technologies (AI/ML, blockchain), data security and compliance frameworks.

Soft Skills:

Outstanding communication, collaboration, and leadership skills.

Strategic thinking and problem-solving abilities with a focus on delivering impactful solutions.

Strong analytical and critical thinking skills.

Ability to influence and inspire teams to achieve goals.