Azure data Architect

Data Architect – Databricks & AWS

• Strong experience in Data Architecture, Data Engineering, Databricks, Apache Spark/PySpark, Python, and Advanced SQL.
• Design and implement scalable ETL/ELT pipelines, data platforms, and Lakehouse architectures using Medallion Architecture.
• Experience with Databricks, Databricks Workflows, Unity Catalog OR Databricks Jobs
• Strong knowledge of Delta Lake, Databricks Workflows, Delta Live Tables (DLT), and dimensional data modeling.
• Hands-on experience with AWS services such as S3, Glue, IAM, Lambda, and CloudWatch.
• Experience with Apache Airflow, Data Warehouse concepts, Git/CI-CD, performance optimization, and data quality.
• Good to have exposure to Kafka/Structured Streaming, Unity Catalog, and modern data governance.

Position: Technical Architect – Data Engineering

Job Summary:

• We are looking for an experienced Technical Architect to lead the design and implementation of modern cloud-based data platforms.
• The ideal candidate should have strong expertise in Azure and/or AWS, Databricks, Snowflake, modern data architecture, and large-scale data engineering.
• The candidate will work closely with business stakeholders, architects, and engineering teams to deliver scalable, secure, and high-performance data solutions.

Key Responsibilities

• Design enterprise-scale data lakehouse and data warehouse architectures.

• Define data ingestion, transformation, and serving architecture.

• Lead architecture discussions and technical governance.

• Design scalable ETL/ELT frameworks using Databricks and Snowflake.

• Define best practices for security, performance, CI/CD, and DevOps.

• Guide engineering teams on implementation.

• Collaborate with business, product, and data governance teams.

Must Have Skills :

• Azure or AWS

• Databricks

• Snowflake

• Data Lakehouse Architecture

• PySpark

• SQL

• Data Modelling

• ETL/ELT Architecture

• Performance Optimization

• CI/CD

• Terraform or Infrastructure as Code (preferred)

Preferred

• Insurance domain

• dbt

• Unity Catalog

• Delta Lake

• Iceberg

• Azure Data Factory / AWS Glue  

Job Description: Associate Director-Data Engineering (Databricks Lakehouse Architect + Cloud Data Engineering Leader)

About our Client -

Client is a leading SAP consulting and digital transformation partner committed to delivering innovative, high-impact solutions across enterprise analytics, cloud, and intelligent business platforms.

As enterprises modernize their data landscapes, the role of traditional data warehousing is rapidly evolving into scalable cloud-native Data Lakehouse architectures. Applexus is expanding its modern data engineering capabilities to help customers integrate enterprise data from SAP and non-SAP ecosystems, build advanced analytics platforms, and enable future-ready AI-driven solutions.

We are looking for an accomplished Databricks Lakehouse Architect / Cloud Data Engineering Leader who can play a key role in this transformation journey — designing modern data platforms, leading cloud data engineering initiatives, and bridging enterprise analytics with next-generation technologies.

The ideal candidate will combine strong hands-on expertise in Databricks, Spark/PySpark, Delta Lake, and Azure/AWS cloud platforms with the ability to engage customers, architect solutions, guide engineering teams, and drive successful delivery.

Role Overview:

We are looking for a hands-on Data Engineering leader who can architect modern cloud data platforms using Databricks Lakehouse and lead solution design, delivery, and engineering teams. This role requires strong technical ownership rather than a pure people management background.

Key Responsibilities:

• Architect scalable Data Lakehouse platforms

• Own solution design, estimation, architecture reviews and client discussions

• Build and optimize enterprise data pipelines

• Provide technical guidance to data engineering teams

• Establish best practices around performance, governance and architecture

Must Have - Databricks Architecture:

• Databricks Lakehouse design

• Delta Lake implementation

• Apache Spark / PySpark engineering

• Medallion architecture (Bronze/Silver/Gold layers)

• Data pipeline optimization

• Unity Catalog and data governance exposure

Cloud Platform Expertise (depth in one required):

Microsoft Azure:

• Azure Databricks

• Azure Data Factory (ADF)

• Azure Data Lake Storage (ADLS)

• Azure Synapse Analytics

OR

Amazon AWS:

• Databricks on AWS

• Amazon S3

• AWS Glue

• Redshift

• Athena

Good to Have:

• Snowflake

• ML Engineering exposure

• Cloud/Data Engineering certifications

Ideal Candidate:

A hands-on architect who can talk to customers, design solutions, estimate projects, guide engineers and review architecture while helping build a modern Data Engineering practice.

 We are looking for an accomplished Databricks Lakehouse Architect / Cloud Data Engineering Leader who can play a key role in this transformation journey — designing modern data platforms, leading cloud data engineering initiatives, and bridging enterprise analytics with next-generation technologies.

The ideal candidate will combine strong hands-on expertise in Databricks, Spark/PySpark, Delta Lake, and Azure/AWS cloud platforms with the ability to engage customers, architect solutions, guide engineering teams, and drive successful delivery.

If you are a hands-on Data Architect who enjoys building modern data platforms and wants to move beyond execution into solution ownership and leadership, I would love to connect.

Key Skills:

Python & System Design: Strong expertise in Python and system design, with proven experience architecting scalable, production-grade systems.

LLM & Agentic AI: Proven experience building LLM-based and agentic systems from the ground up and evaluating them based on reproducibility, calibration, and cost.

Cloud & Data Architecture: Deep understanding of data and cloud architecture across AWS and Azure, including multi-store data design, distributed systems, streaming, security, and cost optimization.

Azure Databricks: Hands-on production experience with Azure Databricks architecture, including Unity Catalog, Delta Lake, cluster policy design, job orchestration, and Terraform provisioning.

Supply Chain & Inventory Management: Strong domain knowledge of supply chain and inventory operations, including demand planning, MRP logic, inventory parameters, and translating business planning decisions into data requirements.

System Architecture & Technical Decision-Making: Ability to make sound architectural decisions based on first principles, evaluate technical trade-offs, and avoid unnecessary complexity and abstraction.

LLM & Agentic AI: Proven experience building LLM-based and agentic systems from the ground up and evaluating them based on reproducibility, calibration, and cost.

Technical Leadership: Ability to influence teams without direct authority, establish technical standards, prepare technical specifications and documentation, and mentor team members.

Experience in pharmaceutical or regulated industries is highly valued.

Technical Lead 

Job Description 

Role Overview 

We are seeking a highly skilled Data Engineering Lead with minimum of 5 years of hands-on experience in Azure data engineering, data warehousing, and automation-driven  integration. The ideal candidate should be a proven technical lead, capable of driving end-to-end 

project delivery and working closely with customer teams. This is a Work from Office / Customer Site role. 

Roles and Responsibilities 

• Lead the design, development, and delivery of data engineering and automation projects. 

• Architect and implement ETL/ELT pipelines using Azure Data Factory. 

• Design and manage enterprise data warehouses including dimensional modeling and 

schema optimization. 

• Manage Azure components including Storage Accounts, Data Lakes, Azure SQL, and Synapse. 

• Drive automation initiatives across data ingestion and transformation workflows. 

• Collaborate with business and technical stakeholders to translate requirements into scalable solutions. 

• Mentor team members and enforce engineering best practices. 

• Serve as the technical anchor responsible for ensuring high-quality, on-time delivery. 

Skills and Qualification 

• Strong hands-on experience with Azure Data Factory, Azure Storage, Azure SQL/Synapse. 

• Deep understanding of data warehousing concepts: star/snowflake schemas, fact/dimension modeling. 

• Experience with automation-led data engineering solutions. 

• Strong troubleshooting, optimization, and analytical skills. 

• Excellent communication and stakeholder management abilities. 

• Proven experience as a Technical Lead leading teams and delivery. 

Must Have 

• Min of 5 years of relevant data engineering experience. 

• Strong Azure Data Engineering and Data Warehousing expertise. 

• Proven Technical Lead experience. 

• Ability to work from office and customer site. 

• Strong ownership mindset with a focus on quality and delivery excellence.

8-12 years experience on Data Engineering role working with Databricks & Azure Cloud technologies.

• Bachelor’s degree in computer science, Information Technology, or related field.

• Strong proficiency in PySpark, Python, SQL.

• Strong experience in data modeling, ETL/ELT pipeline development, and automation • Hands-on experience with performance tuning of data pipelines and workflow

• Proficient in working on Azure cloud components Azure Data Factory, Azure DataBricks, Azure Data Lake etc.

• Experience with data modeling, ETL processes, Delta Lake and data warehousing.

• Experience on Delta Live Tables, Autoloader & Unity Catalog.

Preferred - Knowledge of the insurance industry and its data requirements.

• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.

• Excellent communication and problem-solving skills to work effectively with diverse teams

• Excellent problem-solving skills and ability to work under tight deadlines. 

Responsibilities and JD

Job Description: We are looking for a Senior Developer with strong expertise in PySpark, Databricks, and Snowflake to build scalable data engineering solutions and enterprise data platforms.

Key Responsibilities:

1. Design, develop, and maintain ETL/ELT pipelines using PySpark, Databricks, and Snowflake.
2. Develop batch and real-time data processing solutions for structured and semi-structured data.
3. Build and optimize Databricks notebooks, workflows, and Delta Lake solutions.
4. Design and implement Snowflake databases, schemas, views, stored procedures, tasks, and streams.
5. Develop scalable data models, data marts, and data warehouse solutions.
6. Optimize PySpark jobs, Databricks workloads, and Snowflake queries for performance and cost efficiency.
7. Implement data quality, validation, governance, and security controls.
8. Collaborate with business stakeholders, architects, and cross-functional teams to deliver data solutions.
9. Manage source control and CI/CD deployments using Git and Azure DevOps.
10. Troubleshoot production issues, perform root cause analysis, and ensure pipeline reliability.
11. Mentor junior team members and participate in code reviews and technical design discussions.

Required Skills: PySpark, Databricks, Snowflake, Python, SQL.

Experience: 5+ years of Data Engineering experience with strong hands-on expertise in PySpark, Databricks, and Snowflake.

Lead Data Engineer – Databricks & Azure

• We are looking for a Lead Data Engineer with 5–7 years of experience in Azure, Databricks, and Microsoft Fabric to lead and mentor the data engineering team. The role involves implementing scalable data solutions using Databricks as the core platform, building modern data pipelines, and enabling seamless integration with Microsoft Fabric and Power BI.

Responsibilities & Requirements:

• Lead and mentor data engineers while driving hands-on technical delivery.
• Implement approved Databricks and Microsoft Fabric architectures and solutions.
• Develop metadata-driven bronze, silver, and gold data pipelines.
• Build reusable batch, incremental, CDC, and streaming ingestion pipelines.
• Strong hands-on experience with Azure Databricks, PySpark, SQL, and Delta Lake.
• Experience with Microsoft Fabric, OneLake, Direct Lake, and Power BI integration.
• Implement data quality checks, reconciliation, source-to-target mapping, and metadata management.
• Configure Unity Catalog for data governance, access control, auditing, and lineage.
• Implement CI/CD, automated deployments, and Datadog monitoring.
• Drive testing, documentation, operational readiness, and knowledge transfer.

Good to have:

• Experience with MDM and master data integration.
• Exposure to Azure DevOps or GitHub Actions.
• Experience with automated data testing and reconciliation frameworks.
• Experience working with onshore stakeholders and distributed engineering teams.
• Strong communication, problem-solving, and team leadership skills.

Location: Bangalore Experience: 5 to 7 years Employment type: Full-time, permanent Work Hours: General Shift (10.00 AM to 7.00 PM) website: www.amazech.com Qualifications: Minimum B.E./B.Tech, or higher in Computer Science, Information Technology, Data Engineering, or a related field, with a good academic background. Key Responsibilities: • Design, develop, and maintain end-to-end data pipelines. • Build and optimize ETL/ELT processes for large-scale data processing. • Implement Azure-based data solutions ensuring scalability and performance. • Collaborate with stakeholders to understand business data requirements. • Perform performance tuning and optimization across data platforms. • Support production environments, conduct root cause analysis, and resolve data-related issues. • Maintain comprehensive technical documentation and structured knowledge transfer documents. • Work effectively within Agile/Scrum frameworks and contribute to sprint planning and delivery. • Ensure secure and compliant data handling using Azure best practices. Required Skills & Experience • End-to-end ETL/ELT pipeline development, integration, and performance optimization • Azure Synapse, Azure Logic Apps, Azure SQL, and Azure Databricks, with a strong focus on performance tuning • Microsoft Azure services, including Storage Accounts, Key Vault, and Cognitive Services • Advanced proficiency in Python development and modern productivity tools such as GitHub Copilot and Cursor • Strong documentation discipline, including technical design documentation, and structured knowledge transfer documents • Experience operating within Agile/Scrum frameworks, including production support, root cause analysis, and effective stakeholder collaboration

About Us:

The QX Impact was launched with a mission to make A.I accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them. Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.

Job Summary:

We are looking for a Senior Data Engineer who is creative, collaborative, and adaptable to join our agile team of data scientists, engineers, and UX developers. The role focuses on building and maintaining robust data pipelines to support advanced analytics, data science, and BI solutions.

As a Senior Data Engineer, you will work with internal and external data, collaborate with data scientists, and contribute to the design, development, and deployment of innovative solutions.

Key Responsibilities:

• Design, develop, test, and maintain optimal data pipeline and ETL architectures.
• Map out data systems and define/design required integrations, ETL, BI, and AI systems/processes.
• Prepare and optimize data for predictive and prescriptive modeling.
• Collaborate with teams to integrate ERP data into the enterprise data lake, ensuring seamless flow and quality.
• Enhance cloud data infrastructure on AWS or Azure for scalability and performance.
• Utilize big data tools and frameworks to optimize data acquisition and preparation.
• Build architectures to move data to/from data lakes and data warehouses for advanced analytics.
• Develop and curate data models for analytics, dashboards, and reports.
• Conduct code reviews, maintain production-level code, and implement testing approaches.
• Monitor, troubleshoot, and resolve data ingestion workflows to maintain reliability and uptime.
• Drive innovation and implement efficient new approaches to data engineering tasks.

Must-Have Skills:

• Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field.
• 5+ years of experience working with enterprise data platforms, including building and managing data lakes.
• 3–5 years of experience designing and implementing data warehouse solutions.
• Expertise in SQL, including developing stored procedures (SP) and applying advanced data design concepts.
• Proficiency in Spark (Python/Scala) and Spark Streaming for real-time data pipelines.
• Experience with AWS or Azure services (e.g., AWS Glue, Azure Data Factory, Redshift, Snowflake).
• Familiarity with big data tools such as Apache Kafka, Apache Spark, or Flink.
• Hands-on experience with orchestration tools (e.g., Apache Airflow, Prefect).
• Knowledge of CI/CD processes, version control (e.g., Git, Jenkins), and deployment automation.
• Strong problem-solving, communication, and collaboration skills.

Good-to-Have Skills:

• Experience in integrating ERP data into data lakes.
• Experience with traditional ETL tools (e.g., Talend, Pentaho).

Competencies:

• Tech Savvy - Anticipating and adopting innovations in business-building digital and technology applications.
• Self-Development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.
• Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
• Customer Focus - Building strong customer relationships and delivering customer-centric solutions.
• Optimize Work Processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.

Why Join Us?

• Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
• Work on impactful projects that make a difference across industries.
• Opportunities for professional growth and continuous learning.
• Competitive salary and benefits package.

Application Details

Ready to make an impact? Apply today and become part of the QX Impact team!