Manager - Data engineer (PharmaTech/Life ScienceTech)

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!

About the Role

You'll be at the forefront of designing and implementing robust data platform solutions that power advanced analytics, AI, and machine learning. Working with modern cloud technologies, you'll build scalable data foundations that enable clients to make smarter, data-driven decisions.

Key Responsibilities

• Build scalable data pipelines using Snowflake, AWS, GCP, and Databricks.
• Design and optimize data models for AI and machine learning workloads.
• Develop reliable data foundations for MLOps, governance, and data lineage.
• Integrate data from multiple sources into modern data platforms.
• Leverage Snowpark ML and Snowflake's native AI capabilities.
• Ensure data platforms are secure, scalable, and high-performing.

What We're Looking For

• 5+ years of hands-on experience with Snowflake.
• Strong proficiency in SQL and Python.
• Experience with AWS, Azure, or GCP.
• Knowledge of cloud storage services such as S3, ADLS, or GCS.
• Strong understanding of Dimensional Modeling and Data Vault.
• Experience with Scala or Java is a plus.

Tech Stack

• Data Warehouse: Snowflake
• Programming: SQL, Python, Scala (Good to Have), Java (Good to Have)
• Cloud: AWS, Azure, GCP
• Storage: S3, ADLS, GCS
• AI/ML: Snowpark ML, MLOps

Perks & Benefits

• Public Speaking & Communication Program
• Mentoring Program with Senior Support Leads
• 360° Progress Reviews
• Weekly Learning Sessions & Guilds
• Paid Certifications
• Hackathons & Innovation Days
• Recognition & Rewards Programs
• Team Socials & Annual Offsites
• Employee Assistance Program (24/7 Wellbeing Support)

The Data People Shaping Tomorrow

Our client helps organizations unlock the power of data through modern cloud, analytics, and AI solutions. We believe in creating an environment where talented technologists can learn, innovate, and make a real impact while building cutting-edge data platforms for global clients. If you're passionate about data engineering and want to work with the latest technologies in AI, cloud, and analytics, we'd love to hear from you.

Location – Hyderabad (Hybrid)

Work Experience – 5 to 7 years

CTC – upto 20 LPA

Roles & Responsibilities:

· We are looking for a Senior Data Engineering who will be majorly responsible for designing, building and maintaining ETL/ ELT pipelines.

· Integration of data from multiple sources or vendors to provide the holistic insights from data.

· You are expected to build and manage Data warehouse solutions, designing data models, creating ETL processes, implementing data quality mechanisms etc.

· Performs EDA (exploratory data analysis) required to troubleshoot data related issues and assist in the resolution of data issues.

· Should have experience in client interaction.

· Experience in mentoring juniors and providing required guidance.

Required Technical Skills

· Extensive hands on experience in Python, Pyspark, SQL, Dataiku.

· Strong experience in Data Warehouse, ETL, Data Modelling, building ETL Pipelines, Snowflake database.

· Working knowledge in Databricks, Redshift, ADF etc.

· Hands-on experience in cloud services like Azure, AWS- S3, Glue, Lambda, CloudWatch, Athena.

· Sound knowledge in end-to-end Data management, Data ops, quality and data governance.

· Familiar with SFDC, Waterfall/ Agile methodology.

· Strong domain knowledge in Pharma domain/ life sciences commercial data operations.

Qualifications

· Bachelor’s or master’s Engineering/ MCA or equivalent degree.

· 5-7 years of relevant industry experience as Data Engineer.

· Experience working on Pharma syndicated data such as IQVIA, Veeva, Symphony; Claims, CRM, Sales etc.

· High motivation, good work ethic, maturity, self-organized and personal initiative.

· Ability to work collaboratively and providing the support to the team.

· Excellent written and verbal communication skills.

· Strong analytical and problem-solving skills. 

Design, develop, and maintain ETL pipelines involving large-scale data.

Develop data processing and analytics applications primarily using PySpark and Python.

Build scalable and distributed data processing solutions using Apache Spark.

Develop and deploy data applications on AWS cloud.

Work with AWS services related to storage, compute, ETL, data warehousing, analytics, and streaming.

Implement distributed storage and processing solutions capable of handling high-volume datasets.

Design data processing applications with a focus on performance, scalability, reliability, and optimization.

Work with both SQL and NoSQL databases for data storage, processing, and analytics.

Write, optimize, and analyze SQL, HQL, and NoSQL queries.

Troubleshoot data pipeline and processing issues and ensure data quality and reliability.

Collaborate with data engineers, analysts, architects, and other technical teams to deliver data-driven solutions.

At Mitratech, we are a team of technocrats focused on building world-class products that simplify operations in the Legal, Risk, Compliance, and HR functions. We are a close-knit, globally dispersed team that thrives in an ecosystem that supports individual excellence and takes pride in its diverse and inclusive work culture centered around great people practices, learning opportunities, and having fun! Our culture is the ideal blend of entrepreneurial spirit and enterprise investment, enabling the chance to move at a rapid pace with some of the most complex, leading-edge technologies available.

For over 35 years, the experts at Mitratech have been focused on solving the complex needs. Today, we serve 20,000 client companies of all sizes globally, representing 30% of the Fortune 500 and over 500,000 users in over 160 countries.

As we continue to grow, we’re always looking for resourceful, enthusiastic, and fresh perspectives. Join our global team and see what makes Mitratech a truly exceptional place to work!

Job Overview 

Principal Data Engineer

About Engineering at Mitratech Legal Solutions 

Mitratech's engineering organization is a collaborative and dynamic environment where engineers are empowered to drive technical direction and innovation. Our engineers are passionate about delivering high-quality products and solutions that meet the evolving needs of our customers, and we're committed to fostering a culture of continuous learning and growth. 

About the Role 

Mitratech is a fast-paced and dynamic environment, and this role requires someone who is adaptable, resilient, and able to thrive in a rapidly changing landscape. If you’re a seasoned engineer with a passion for technical leadership, innovation, and collaboration — including building the data foundations that power trusted reporting and agentic AI-driven products — we’d love to hear from you. 

What You Will Do

•  Drive technical direction for a significant product domain or platform capability, ensuring alignment with business objectives and customer needs 

•  Design and maintain data pipelines and reporting models that power trusted business metrics and increasingly feed agentic AI systems (e.g., RAG ingestion, embeddings, vector stores, AI agent workflows) 

•  Use AI-assisted and agentic engineering tools (e.g., Claude Code, Copilot, Cursor, AI agents) as part of your own workflow, and help other engineers adopt agentic development practices effectively 

•  Reduce systemic complexity by identifying and leading architectural debt remediation, and developing strategies for ongoing technical debt management 

•  Partner with Product and Engineering leadership to inform multi-quarter roadmap feasibility, and provide technical guidance and oversight to ensure successful implementation 

•  Elevate engineering craft across multiple teams through RFCs, mentorship, and knowledge sharing, and develop training programs to improve engineering skills and knowledge 

•  Represent Mitratech’s technical capabilities externally, including speaking at conferences, contributing to open-source projects, and engaging with industry peers and thought leaders 

What We Are Looking For 

To be successful in this role, you will need: 

•  10+ years of experience in software engineering, with a focus on technical leadership and architecture 

•  Deep understanding of data engineering principles, including data modeling, data warehousing, reporting, and data governance 

•  Strong technical expertise in SQL, PostgreSQL, ETL/ELT pipelines, BI tools, and analytics platforms 

•  Practical experience with AI/LLM-adjacent and agentic AI data work — e.g., RAG ingestion pipelines, embedding generation, vector store management, or building/operating AI agent workflows over data — using AI coding assistants (Claude Code, Copilot, Cursor, or similar) as a regular part of the engineering workflow 

•  Working knowledge of modern cloud platforms such as AWS 

•  Experience with BI, reporting, dashboards, and customer-facing analytics 

•  Experience leading cross-functional initiatives with product, engineering, analytics, and business teams 

Nice to Have 

•  Working knowledge of Ruby on Rails and React 

•  Experience with a semantic or metrics layer (e.g., dbt Semantic Layer, headless BI) 

•  Understanding of CI/CD, Git-based workflows, and infrastructure-as-code 

The Stack Context 

•  Modern data stack: Fivetran, Airbyte, dbt, Snowflake, GitHub, Terraform, or similar tools 

•  Application context (nice to have): Ruby on Rails, React, or similar backend/frontend frameworks 

•  Data modeling: SQL, analytics models, documentation, testing, naming standards, and version control 

•  Infrastructure: cloud-based data infrastructure, infrastructure-as-code, CI/CD, monitoring, and cloud storage 

•  Data workflows: ingestion, transformation, orchestration, reporting, deployment, and change management 

•  Reporting focus: trusted metrics, scalable reporting models, dashboards, exports, and data quality 

•  AI surface: data pipelines and quality practices supporting AI/LLM and agentic AI use cases (RAG, embeddings, vector stores, AI agents) alongside traditional BI 

Why This Role 

This role offers a unique opportunity to drive technical direction and innovation at a rapidly growing company, while also mentoring and coaching engineers to improve their craft. As a Principal Data Engineer at Mitratech, you will have the chance to work on complex and challenging problems spanning trusted reporting and agentic AI systems, collaborate with cross-functional teams, and represent the company's technical capabilities externally. If you're looking for a role that offers a mix of technical leadership, data and reporting depth, agentic AI innovation, and collaboration, this could be the perfect fit for you. 

We are an equal-opportunity employer that values diversity at all levels. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity, disability, or veteran status.

• Design, build, and maintain scalable ETL/ELT pipelines for batch and real-time data ingestion and transformation.
• Develop and optimize data lake and data warehouse architectures (e.g., Snowflake, BigQuery, Redshift).
• Work with cloud platforms GCP, Azure to manage data infrastructure.
• GCP as mandatory skills
• Collaborate with analytics and product teams to understand data needs and deliver solutions.
• Ensure data quality, reliability, security, and compliance across all data systems.
• Mentor junior data engineers and contribute to best practices and code reviews.
• Monitor and troubleshoot data pipeline performance and resolve data-related issues.
• Automate data validation, monitoring, and alerting processes.
• 8+ years of experience in data engineering or software engineering with a data focus.
• Proficient in SQL and at least one programming language (e.g., Python, Scala, Java).
• Experience with modern data warehousing tools (e.g., Snowflake, Redshift, BigQuery).
• Strong understanding of data modeling, data lakes, and ETL/ELT design.
• Hands-on experience with orchestration tools like Airflow, dbt, or similar.
• Solid experience with cloud data platforms (AWS/GCP/Azure).
• Familiarity with CI/CD pipelines, containerization (Docker/Kubernetes), and version control (Git).
• Experience working in a DevOps or DataOps environment.
• Knowledge of data governance, lineage, and cataloging tools (e.g., Collibra, Alation).
• Familiarity with streaming technologies (Kafka, Spark Streaming, Flink).
• Experience supporting machine learning workflows and data science initiatives.

About AuxoAI:

AuxoAI is a global platform-based services firm. We help companies—turn their strategies into practical digital and AI solutions. By understanding how our clients make decisions, we use digital and Artificial Intelligence (AI) technologies to drive growth, enhance their operations, improve customer experiences, and provide clear, actionable insights from their data. What We Do We work across various industries such as healthcare, high-tech, consumer packaged goods (CPG), finance etc., and in sales, marketing, and customer support functions.

We help our clients with accelerating their digital and AI journeys through:

• AI Application Development

• Data, Digital and Cloud acceleration using AI

• AI Native Product Engineering

We are seeking a skilled and experienced Data Engineer to join our dynamic team. The ideal candidate will have 6+ years of prior experience in data engineering, with a strong background in AWS (Amazon Web Services) technologies. This role offers an exciting opportunity to work on diverse projects, collaborating with cross-functional teams to design, build, and optimize data pipelines and infrastructure.

Responsibilities:

* Design, develop, and maintain scalable data pipelines and ETL processes leveraging AWS services such as S3, Glue, EMR, Lambda, and Redshift.

* Collaborate with data scientists and analysts to understand data requirements and implement solutions that support analytics and machine learning initiatives.

* Optimize data storage and retrieval mechanisms to ensure performance, reliability, and cost-effectiveness.

* Implement data governance and security best practices to ensure compliance and data integrity.

* Troubleshoot and debug data pipeline issues, providing timely resolution and proactive monitoring.

* Stay abreast of emerging technologies and industry trends, recommending innovative solutions to enhance data engineering capabilities.

Requirements :

* Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

* 6+ years of prior experience in data engineering, with a focus on designing and building data pipelines.

* Proficiency in AWS services, particularly S3, Glue, EMR, Lambda, and Redshift.

* Strong programming skills in languages such as Python, Java, or Scala.

* Experience with SQL and NoSQL databases, data warehousing concepts, and big data technologies.

* Familiarity with containerization technologies (e.g., Docker, Kubernetes) and orchestration tools (e.g., Apache Airflow) is a plus.

Data Engineer

Data Lakehouse & Platform Engineering 

About the Role

We are hiring Data Engineer to own the lifecycle of our enterprise Data Lakehouse platform. We are looking for engineers who think in systems, make platform-level design decisions, and can build and operate a production-grade, multi-source lakehouse from the ground up, covering ingestion through consumption across a complex, multi-cloud source landscape.

You will be the technical authority for a platform that consolidates data from 18+ enterprise products (Costpoint, GovWin, Specpoint, Vantagepoint, and others) into a governed, medallion-architected data lake on AWS S3 with Apache Iceberg table format, orchestrated via AWS Step Functions, and queryable through AWS Athena and Trino. This role is end-to-end: you own ingestion, transformation, quality, orchestration, ML data supply, and BI consumption.

Key Responsibilities

•      Architect and evolve the full medallion lakehouse — Bronze, Silver, and Gold layers — on AWS S3 with Apache Iceberg; own schema design, partitioning, compaction, and retention policies.

•      Design and implement scalable Glue ETL (PySpark) pipelines for bronze_to_silver and silver_to_gold transformations, incorporating dbt for SQL-layer transformations where appropriate.

•      Own and extend CDC ingestion via Fivetran; manage schema evolution, connector health, and sync reliability across 18+ source products.

•      Build and maintain AWS Step Functions state machines and EventBridge schedules for end-to-end pipeline orchestration; implement Lambda-based quality and drift monitors.

•      Govern the Glue Catalog and Lake Formation policies; enforce column-level security, row-level access controls, and audit logging to meet SOC2 and regulatory requirements.

•      Architect the query layer — optimize Athena workgroups and partition pruning; plan and execute Trino-on-EKS deployment for sub-second analytics workloads.

•      Partner with data science teams on SageMaker data supply: feature engineering pipelines, training dataset preparation, and model registry integration.

•      Implement real-time and near-real-time streaming solutions using Kafka or Kinesis where sub-13-minute latency is required.

•      Lead platform modernization initiatives: evaluate emerging formats (Iceberg vs. Delta Lake vs. Hudi), tooling, and cost optimization strategies.

•      Establish and enforce data engineering best practices: code reviews, CI/CD for pipeline code, IaC (Terraform / CloudFormation), and incident response runbooks.

•      Mentor and level up junior and mid-level data engineers; define team standards for pipeline design, testing, and documentation.

Required Qualifications

•      Software or data engineering experience, with at least 4 years in an architect or technical lead capacity designing large-scale cloud data platforms.

•      Deep, hands-on expertise with AWS data services: S3, Glue (PySpark ETL), Athena, Step Functions, Lambda, EventBridge, Lake Formation, SageMaker, and CloudWatch.

•      Production experience with Apache Iceberg (or Delta Lake / Hudi) table formats — compaction, snapshot management, schema evolution, and time travel.

•      Strong PySpark and Python skills; ability to write, review, and optimize distributed data processing jobs at scale.

•      Hands-on experience with CDC-based ingestion platforms (Fivetran, Debezium, or equivalent) across heterogeneous source systems.

•      Proven experience designing and implementing medallion (Bronze/Silver/Gold) or equivalent multi-hop lakehouse architectures.

•      Experience with data pipeline orchestration: AWS Step Functions, Apache Airflow, or equivalent; event-driven pipeline design patterns.

•      Strong SQL skills; experience with Athena, Trino, Presto, or equivalent query engines for large-scale analytical workloads.

•      Familiarity with data governance tooling: catalog management (Glue Catalog, Apache Polaris/Iceberg REST), data lineage, access controls, and audit frameworks.

•      Experience with Infrastructure as Code (Terraform or CloudFormation) for data platform provisioning and drift management.

•      Solid understanding of dimensional modeling, schema design (star/snowflake), and data normalization for BI and analytics workloads.

•      Bachelor's degree in Computer Science, Engineering, or a related field; or equivalent professional experience.

Preferred Qualifications

•      Experience operating Trino or PrestoDB on Kubernetes (EKS); tuning for sub-second query latency and multi-tenant workloads.

•      Familiarity with streaming platforms (Kafka, Kinesis, or Pub/Sub) and real-time lakehouse patterns.

•      Experience with Apache Polaris or other Iceberg REST catalog implementations.

•      Exposure to SageMaker MLOps pipelines, Model Registry, and feature store patterns for ML data supply.

•      Experience with dbt (data build tool) for SQL-layer transformation and documentation in lakehouse environments.

•      Government contracting or ERP domain knowledge (Costpoint, Deltek, Oracle, or similar enterprise platforms) is a strong plus.

•      AWS certifications: Data Engineer Associate, Solutions Architect Professional, or equivalent.

What You Will Build

You will be a founding architect of a strategic, cross-product data platform that serves 18+ enterprise applications and their analytics, ML, and AI workloads. The decisions you make on schema, storage format, query layer, governance, and orchestration will shape the data foundation of the company for years. This is a high-impact, high-ownership role with direct visibility to senior leadership.

Job Title : Senior Data Engineer – Databricks

Experience : 14 to 20 Years

Location : HSR Layout, Bangalore

Work Mode : Hybrid – 3 Days WFO

Shift : 11:30 AM – 07:30 PM IST

Positions : 2

Notice Period : Immediate Joiners Only

Interview : 1 Technical Round + 2 Client Rounds

Role Overview :

We are looking for a Senior Data Engineer to build and lead enterprise-scale data platforms for a Switzerland-based commodity client.

The role requires a strong hands-on Data Engineering professional with expertise in Databricks, PySpark, Python, SQL, and AWS, along with technical leadership and stakeholder management experience.

Must-Have Skills :

• 14 to 20 years of Data Engineering experience
• Databricks & Apache Spark / PySpark
• Python & SQL
• AWS Cloud
• Lakehouse Architecture
• ETL / ELT & Distributed Data Processing
• Batch & Streaming Pipelines
• Data Pipeline Optimization & Data Modeling
• CDC & Incremental Processing
• Git, CI/CD & Testing
• Data Quality, Monitoring & Observability
• Technical Leadership & Stakeholder Management

Key Responsibilities :

• Design and build scalable data pipelines using Databricks, PySpark, Python, SQL, and AWS.
• Own data products from design through production.
• Develop batch / streaming pipelines and reusable ETL / ELT frameworks.
• Optimize pipelines for performance, scalability, reliability, and cost.
• Design scalable data architectures and data models.
• Implement data quality, monitoring, lineage, and CI/CD practices.
• Lead technical discussions and mentor engineering teams.
• Collaborate with business stakeholders, architects, product owners, and engineering teams.
• Remain hands-on while providing technical leadership.

Ideal Candidate :

A 14 to 20 years experienced, hands-on Data Engineering leader with strong Databricks + PySpark + AWS expertise, excellent communication, stakeholder management, and experience delivering enterprise-scale data platforms.

🔴 Super Urgent : Only Bangalore-based immediate joiners.

Role Summary:

We are looking for an experienced Snowflake Lead to lead the design, development, migration, and optimization of enterprise data platforms using Snowflake. The candidate will provide technical leadership to data engineering teams and work closely with architects, business stakeholders, and application teams.

Key Responsibilities

• Lead the architecture and development of scalable Snowflake data warehouse solutions.
• Design and develop scalable Azure Data Factory (ADF) pipelines for API-based and batch data ingestion, implementing parameterized workflows, scheduling, and error handling.
• Build and optimize enterprise Snowflake data warehouse solutions using Snowflake SQL, Streams, Tasks, Stored Procedures, VARIANT data type, and LATERAL FLATTEN for semi-structured JSON processing.
• Integrate GraphQL and REST APIs using OAuth 2.0, implementing secure API authentication, JSON parsing, and API validation using Postman.
• Develop cloud-based data ingestion solutions using Azure Data Lake Storage Gen2 (ADLS) as the landing layer and Azure Key Vault for secure credential management.
• Design metadata-driven ELT frameworks with incremental loading, audit logging, watermark processing, and automated data orchestration.
• Optimize Snowflake performance through warehouse sizing, query tuning, clustering strategies, Time Travel, Cloning, and warehouse management best practices.
• Collaborate with DevOps teams using Azure DevOps for source control, CI/CD deployment, release management, and Agile delivery.
• Design dimensional data models, build curated data marts, and support enterprise reporting and analytics requirements.
• Develop and maintain Power BI semantic models, datasets, dashboards, and reports; knowledge of DAX, Power Query, and data visualization best practices is preferred.
• Work closely with business stakeholders, solution architects, and cross-functional teams to deliver secure, scalable, and high-performance cloud data platform solutions.

Thanks,

Mounika P