Data Engineering

Job Title: Senior Data Architect

Experience: 7+ Years

Location: India (Ahmedabad / Hybrid/Remote)

Job Summary

We are looking for an experienced Senior Data Architect to support the modernization and enhancement of Enterprise Analytic Data Warehouse (ADW). The candidate will be responsible for evaluating existing data architecture, designing scalable data models, assessing data integration across clinical, operational and financial domains, and establishing data governance and data quality standards.

Key Responsibilities

• Assess and review the existing Enterprise Analytic Data Warehouse architecture, database structures and data integration processes.
• Design and improve enterprise data models covering clinical, operational, financial and revenue-cycle information.
• Define data architecture standards, database structures, data relationships and integration strategies.
• Evaluate data flows between source systems and the data warehouse.
• Design and review source-to-target mappings and data lineage.
• Identify architectural gaps affecting data completeness, consistency, integrity and reporting accuracy.
• Establish standardized data definitions, data governance practices and metadata management.
• Ensure consistent patient, facility, payer and other critical identifiers across different datasets.
• Support integration of billing, claims, payment, denial and accounts receivable (AR) data.
• Work with SQL and Python-based data processing solutions to investigate and validate data structures.
• Recommend improvements to warehouse scalability, performance, reliability and maintainability.
• Develop a prioritized architecture and modernization roadmap for future implementation.
• Coordinate with data engineers, analytics engineers and business stakeholders.

Required Technical Skills

• Strong experience in Data Architecture and Enterprise Data Warehousing.
• Advanced SQL and relational database concepts.
• Experience with data modelling (conceptual, logical and physical).
• Knowledge of ETL/ELT pipelines and data integration.
• Experience with data profiling, data lineage and metadata management.
• Understanding of data governance, data quality and data validation frameworks.
• Experience working with large and complex datasets.
• Python knowledge for data analysis and validation.
• Experience with cloud-based data platforms or modern data warehouse technologies.

Preferred Skills

• Experience with Databricks, Azure, AWS or similar cloud data platforms.
• Experience with healthcare data warehouses.
• Knowledge of clinical, financial, billing and claims datasets.
• Understanding of HIPAA, PHI and healthcare data security principles.
• Experience with healthcare analytics, reimbursement and revenue-cycle data.

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.

Role: Technical Architect – Data & Cloud

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.

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 optimization, CI/CD, and DevOps.
• Provide technical guidance to engineering teams during implementation.
• Collaborate with business, product, architecture, and data governance teams.

Must-Have Skills:

• Azure and/or AWS
• Databricks
• Snowflake
• Data Lakehouse Architecture
• PySpark
• SQL
• Data Modelling
• ETL/ELT Architecture
• Performance Optimization
• CI/CD
• Terraform / Infrastructure as Code, preferred

Preferred Skills:

• Insurance domain experience
• dbt
• Unity Catalog
• Delta Lake
• Iceberg
• Azure Data Factory / AWS Glue

Job Overview:

We are seeking an experienced Cloud Data Engineer to the architecture, development, Data migration, ETL pipeline in cloud and optimization of a next-generation data platform. This is a development role for an individual with over 4 years of deep data engineering and data migration, data pipeline in AWS expertise, capable of driving technical direction, and delivering high-impact solutions in a fast-paced

4+ Years of hands-on, progressive experience in Cloud Data Engineering, cloud ecosystems AWS, Data Architecture

• Deep conceptual understanding of core data engineering principles, ETL/ELT patterns, and metadata management

•  Ability to translate complex business needs into actionable technical requirements.

•  Strong troubleshooting and problem-solving skills in distributed systems.

•  Agile/Scrum teamwork capabilities and version control practices

• Insurance industry experience preferred but not mandatory

• Tools:

o Cloud Environment: AWS (S3, IAM, VPC, Glue, Lambda etc.)

o Experience with dbt Core, Iceberg, AWS Glue Catalog, AWS lambda, Redshift, Athena, Splunk, AmazonQ, AWS streaming services, Git

o Strong SQL, Pyspark and Python

Designation: Data Architect

Reporting: VP, Engineering

Desired Experience: 12 – 18 Years

Qualification: BE/ B Tech/ M Tech/ MCA and any Graduate.

Job Location: Noida Sec-6 (Nearest Metro Station 15)

(WFH/Work from Home Available)

Total Employees: 100+ Members

Working Days: Monday to Friday

Key Responsibilities

• Define, own, and evolve the enterprise data architecture
• Design scalable, secure, high-performance end-to-end data platforms
• Establish data modeling standards (conceptual, logical, physical)
• Act as architectural authority for data pipelines, APIs, and integrations
• Ensure platform design meets security, compliance, availability, and cost-efficiency standards
• Define and enforce data governance, data quality, metadata, lineage, and master data principles
• Collaborate with Data Engineers for implementation of architecture designs
• Align data architecture with product roadmaps and business priorities
• Define standards for data sharing, data products, and external data exposure
• Contribute to long-term data platform roadmap and technology adoption
• Support leadership with architecture reviews and strategic decisions

Required Experience & Technical Expertise

Experience

• 12+ years in Data domain
• 3–5 years as Data Architect / Lead Data Role
• Experience designing enterprise-scale data platforms

Data Architecture & Modeling

• Deep expertise in Data Modeling & Data Warehousing
• Advanced SQL knowledge
• Strong experience with Snowflake & modern cloud data stacks
• Experience with relational and cloud-native databases

Security & Compliance

• Knowledge of Data Security (Dynamic Masking, Row-Level Security, Access Control)
• Strong understanding of GDPR & Data Privacy regulations

Integration & Engineering

• Experience with streaming & event-driven architectures
• APIs & integration patterns (REST, event-based systems)
• Familiarity with CI/CD, DevOps & Infrastructure-as-Code in data environments
• Architecture reviews & technology evaluations

Key Technical Skills (Must Have)

• Snowflake
• Matillion (or equivalent data integration tools)
• Python
• SQL
• REST APIs & Event-driven integrations
• Power BI / Qlik / Tableau
• Experience with CRM / Marketing Automation / PIM platforms
• Agile & Continuous Delivery practices

Personal Skills

• Strong architectural mindset with focus on scalability
• Collaborative leadership ability
• Analytical and business-oriented thinking
• Strong communication skills (technical & non-technical stakeholders)
• Proactive, autonomous, and accountable

Why Join Us?

• Work with best-in-class data & cloud technologies
• Influence core data architecture of a global digital platform
• Strong engineering culture focused on ownership & quality
• Hybrid work model (mostly remote)
• 25+ years of industry leadership with strong growth trajectory

 Please fill the following details:

1) Current CTC

2) Expected CTC

3) Notice Period

4) Current Location

5) Reason of Change

6) Years of Experience

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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  

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!

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.

We are looking for a dynamic Data Engineer to join our team of technology enthusiasts. You will leverage data to drive strategic decision-making and pioneering solutions, working with complex datasets, collaborating closely with stakeholders, and transforming data into actionable insights to drive innovation.

Qualifications and Skills:

• Minimum 5 years of experience as a Data Engineer
• Hands-on experience with Azure cloud-based data solutions
• Expertise in database design and management, including SQL databases such as SQL Server
• Proficient in ETL (Extract, Transform, Load) design for data integration and processing
• Strong knowledge of data modeling principles and techniques
• Ability to analyze and translate data into actionable insights, reports, and visualizations
• Proficiency in Power BI for reporting and data visualization

Desirable Skills:

• Experience with Power BI Report Builder / Reporting Services
• Knowledge of statistical analysis or Data Science
• Experience within the UK Insurance industry is a plus
• Python or R coding skills

Responsibilities:

• Implement efficient data exchange between internal and external systems to increase efficiency and reduce re-keying and translation errors
• Support the Broking business by developing high-quality information resources, ensuring data availability and accessibility for decision-making
• Engineer data inputs and outputs from core applications and semi-structured remote service data through data syncs between data lake, ODS (SQL database), and leveraging Fabric and ADF
• Perform data engineering tasks including ingestion, cleansing, and collation from a wide range of internal and external sources
• Implement different methods of streaming data and create reconciliations for datasets
• Build analytical models to support reporting and analytics
• Collaborate with an agile delivery team to work on the backlog of specified work

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.