Blockchain Data and ML Engineer

Job Summary

We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate should have strong expertise in SQL, Python, Linux, and modern data engineering practices to support data integration, transformation, and analytics.

Key Responsibilities

• Design, develop, and maintain ETL/ELT data pipelines.
• Write efficient and optimized SQL queries for data extraction, transformation, and reporting.
• Develop automation scripts using Python for data processing and workflow optimization.
• Work with Linux environments for deployment, monitoring, and troubleshooting.
• Ensure data quality, integrity, and reliability across data platforms.
• Collaborate with data analysts, software engineers, and business stakeholders to deliver data solutions.
• Monitor, troubleshoot, and optimize data pipelines for performance and scalability.
• Implement best practices for data security, governance, and documentation.

Required Skills

• Strong experience in Data Engineering concepts and ETL/ELT processes.
• Proficiency in SQL, including query optimization and database design.
• Strong programming skills in Python.
• Hands-on experience with Linux commands, shell scripting, and system administration basics.
• Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
• Familiarity with Git/version control.
• Strong analytical and problem-solving skills.

Preferred Skills

• Experience with cloud platforms (AWS, Azure, or GCP).
• Knowledge of Apache Spark, Airflow, Kafka, or similar data engineering tools.
• Experience with data warehousing solutions and big data technologies.
• Understanding of CI/CD pipelines and containerization (Docker/Kubernetes).

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• Relevant certifications in cloud or data engineering are an added advantage.

Data Engineer Short Hiring Post

🚨 Hiring: Data Engineer

🔹 Experience: 5–9 Years

🔹 Location: Bangalore / Hyderabad

🔹 Skills: PySpark, Python, SQL, ETL, CI/CD, Data Modeling

🔹 Process: L1 Virtual → L2 F2F Karat Test

🔹 F2F: Bangalore / Hyderabad Location

🔹 Positions: Immediate requirement

⚠️ Note: Candidates must be available for F2F Karat immediately after L1.

#Hiring #DataEngineer #PySpark #Python #SQL #BangaloreJobs #HyderabadJobs #Mphasis #ImmediateJoiners

1st virtual , 2nd round F2F

Python pyspark, SQL, data engineer

5+yrs

Bang/hyderabad

immediate to 15days.

We are looking for a talented and driven Data Scientist to join our growing Analytics team in India. In this role, you will work at the intersection of advanced machine learning, scalable MLOps infrastructure, and domain-specific healthcare analytics. You will collaborate closely with cross-functional teams to build, deploy, and maintain production-grade ML models that drive real-world impact in clinical trials and healthcare operations.

KEY RESPONSIBILITIES

End-to-End ML Development

•     Design, build, and optimize predictive models across the full ML lifecycle—from data ingestion to model serving.

•     Conduct rigorous Exploratory Data Analysis (EDA) to surface insights and drive feature engineering decisions.

•     Validate model performance using appropriate statistical techniques and domain knowledge.

MLOps & Production Deployment

•     Deploy, monitor, and maintain production-grade ML models using Databricks MLFlow endpoints and Unity Catalog.

•     Implement CI/CD pipelines for model versioning, experiment tracking, and automated retraining.

•     Ensure model reliability, observability, and performance in live production environments.

Language Models & LLM Applications

•     Apply transformer-based models (BERT, ClinicalBERT, Trial2Vec) for NLP tasks including classification, NER, and information extraction.

•     Build and maintain vector similarity search pipelines for semantic retrieval and recommendation use cases.

•     Fine-tune pre-trained models for domain-specific applications in clinical and healthcare contexts.

•     Support exploratory work around LLM integration and prompt engineering for internal tooling.

Domain-Driven Analytics

•     Apply advanced analytics within complex healthcare and clinical trial datasets—including patient records, trial protocols, and adverse event data.

•     Translate ambiguous business problems into structured analytical frameworks with measurable outcomes.

•     Partner with domain experts, product managers, and engineering teams to deliver data-driven solutions.

REQUIRED QUALIFICATIONS

Education

•     Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Bioinformatics, or a closely related field.

Experience

•     2–4 years of hands-on experience in a data science or machine learning role.

•     Demonstrable experience deploying ML models in production environments (not just prototyping).

Technical Skills

•     Strong proficiency in Python (pandas, NumPy, scikit-learn, PyTorch / TensorFlow).

•     Experience with Databricks, MLFlow (experiment tracking, model registry, endpoints), and Unity Catalog.

•     Hands-on experience with BERT-family models and Hugging Face Transformers library.

•     Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embedding-based retrieval.

•     Solid understanding of SQL and working with large structured/unstructured datasets.

•     Exposure to cloud platforms (AWS / GCP / Azure) and distributed computing frameworks (Spark).

GOOD TO HAVE

•     Prior experience with clinical trial data standards (CDISC, CDASH, SDTM) or healthcare ontologies (SNOMED, ICD-10).

•     Familiarity with Trial2Vec or similar trial-to-vector embedding approaches.

•     Experience with LLM fine-tuning, RAG pipelines, or prompt engineering in a production setting.

•     Knowledge of regulatory and compliance considerations in healthcare AI (e.g., FDA guidelines, HIPAA).

•     Contributions to open-source ML projects or published research.

THIS ROLE IS NOT FOR YOU IF…

•     You have strong SQL/BI skills but limited hands-on ML modelling experience — or you’ve built models only in notebooks without ever deploying them to production.

•     Your LLM exposure is limited to API calls and prompt engineering — with no experience fine-tuning models, working with embeddings, or building vector search pipelines.

Job Description: Python + AI

Company: Wissen Technology

Location: Bangalore, India

Experience: 5+Years

Employment Type: Full-Time

Role: Python + AI / Data Engineer

About the Role

Wissen Technology is looking for experienced Python + AI / Data Engineering professionals to join our technology team in Bangalore. The ideal candidate will have strong hands-on experience in Python, Artificial Intelligence, Generative AI, PySpark, Snowflake, and data pipeline development.

The candidate should be capable of designing and developing scalable data and AI solutions, building robust ETL/ELT pipelines, working with large datasets, and integrating AI/ML capabilities into enterprise applications.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Python and PySpark.
• Develop robust ETL/ELT pipelines for processing large volumes of structured and unstructured data.
• Build and optimize data processing solutions using Apache Spark / PySpark.
• Develop data ingestion and transformation pipelines into Snowflake.
• Design and implement scalable Snowflake data models, tables, views, and SQL transformations.
• Work with batch and, where applicable, real-time data processing pipelines.
• Build and integrate AI and Generative AI solutions using Python.
• Develop LLM-based applications, RAG solutions, AI agents, and AI-powered services.
• Integrate AI models with enterprise data platforms and data pipelines.
• Develop REST APIs and microservices using FastAPI, Flask, or Django.
• Perform data cleansing, transformation, validation, and quality checks.
• Optimize PySpark jobs, SQL queries, Snowflake workloads, and data pipelines for performance and scalability.
• Implement data pipeline monitoring, logging, error handling, and alerting.
• Work with cloud platforms such as AWS, Azure, or GCP.
• Collaborate with Data Scientists, Data Engineers, Software Engineers, Architects, and business stakeholders.
• Participate in technical design, architecture, code reviews, and production support.
• Mentor junior engineers and contribute to engineering best practices.

Preferred Qualifications

• Bachelor's or master's degree in computer science, Engineering, Data Science, Artificial Intelligence, or a related field.
• Experience working on enterprise-scale AI and data engineering projects.
• Experience combining Python + PySpark + Snowflake + AI/GenAI in production environments.
• Experience with Databricks is an advantage.
• Experience with AI Agents / Agentic AI and tool/function calling.
• Knowledge of distributed systems and cloud-native architecture.
• Experience leading technical initiatives or mentoring engineering teams.

Description

We’re seeking a highly skilled, execution-focused Senior Data Scientist with a minimum of 5 years of experience. This role demands hands-on expertise in building, deploying, and optimizing machine learning models at scale, while working with big data technologies and modern cloud platforms. You will be responsible for driving data-driven solutions from experimentation to production, leveraging advanced tools and frameworks across Python, SQL, Spark, and AWS. The role requires strong technical depth, problem-solving ability, and ownership in delivering business impact through data science.

Responsibilities

• Design, build, and deploy scalable machine learning models into production systems.
• Develop advanced analytics and predictive models using Python, SQL, and popular ML/DL frameworks (Pandas, Scikit-learn, TensorFlow, PyTorch).
• Leverage Databricks, Apache Spark, and Hadoop for large-scale data processing and model training.
• Implement workflows and pipelines using Airflow and AWS EMR for automation and orchestration.
• Collaborate with engineering teams to integrate models into cloud-based applications on AWS.
• Optimize query performance, storage usage, and data pipelines for efficiency.
• Conduct end-to-end experiments, including data preprocessing, feature engineering, model training, validation, and deployment.
• Drive initiatives independently with high ownership and accountability.
• Stay up to date with industry best practices in machine learning, big data, and cloud-native deployments.

Requirements

• Minimum 5 years of experience in Data Science or Applied Machine Learning.
• Strong proficiency in Python, SQL, and ML libraries (Pandas, Scikit-learn, TensorFlow, PyTorch).
• Proven expertise in deploying ML models into production systems.
• Experience with big data platforms (Hadoop, Spark) and distributed data processing.
• Hands-on experience with Databricks, Airflow, and AWS EMR.
• Strong knowledge of AWS cloud services (S3, Lambda, SageMaker, EC2, etc.).
• Solid understanding of query optimization, storage systems, and data pipelines.
• Excellent problem-solving skills, with the ability to design scalable solutions.
• Strong communication and collaboration skills to work in cross-functional teams.

Benefits

• Best-in-class salary: We hire strong talent and compensate accordingly.
• Proximity Talks: Meet and learn from designers, engineers, product leaders, and AI practitioners.
• Continuous learning: Work with a world-class team and stay close to the latest in AI, engineering, and product development.
• High-impact work: Build AI-first systems and products used at scale by global clients.

About Us

Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world. We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore.

Since 2019, Proximity has built high-impact, scalable products used by millions of users every day. Today, we are a global team of engineers, designers, product managers, and experts solving complex problems and building cutting-edge technology at scale.

About LH2 AI LabsLH2 AI Labs is an applied research lab solving data platform and curation challenges for foundation model development. We serve every frontier AI lab with the mission of delivering the best data to power the best models.

Our customers are the ones building the foundation models themselves and our work sits directly in the loop of how those systems improve. This is a rare opportunity to join a company at a defining moment in AI.

About the role:

This is a full-time, hands-on role where you will own the core infrastructure and systems that enable us to discover customers' data landscape, handle sensitive data like names, address securely and to clean and catalog them into training-ready datasets.

That path covers connectors and on-prem agentic discovery components, secrets and PII scrubbing, scale and cost efficient ingestion and clearance for use in model training. You lead a small team of 3-4 engineers and raise the quality bar in your pod.

What you'll own

• Connectors and extraction - You'll build connectors for common SaaS and databases (Google Workspace, Slack, Postgres/MySQL, Jira, MongoDB) and for specific tools such as Razorpay, GreytHR, Keka, Zoho and LeadSquared. The rule is to build only where no good open-source connector or clean export exists.
• On-prem scanning - You'll build a CLI or agent that runs at the data owner's end to sample and estimate the value of their data without shipping all of it to us.
• Clearance pipeline - Secrets detection across full git history, fail-closed. PII redaction for code and conversational data, including Indian identifiers (PAN, Aadhaar, GSTIN, IFSC, UPI). Measurable recall and precision.
• Lineage - Every output record must trace back to its raw source, and every lot must be revocable.
• Delivery - Packaging, sampling for buyers, and supporting the supply and BD teams on data questions.

You have

• 8+ years in backend or data engineering, with at least 2 years leading up to 4 or more engineers.
• You've built ingestion or ETL pipelines that run in production.
• Hands-on work with sensitive data such as PII, financial or health data, including redaction, masking or access controls.
• The judgment to decide what to build and what to adopt.

Nice to have

• Experience with Presidio, gitleaks/TruffleHog, dlt or Airbyte.
• Knowledge of DPDP, GDPR, HIPAA or SOC 2.
• You've shipped software that runs in customers' environments.

This is not a pure people-management role. You'll write code, review everything, and personally own the hardest problems in the pod.

Role Overview

We are looking for an AI/ML Engineer with 2 - 6 years of industry experience to develop and deploy machine learning solutions for industrial and smart manufacturing use cases. The role involves working with real-world industrial data, developing predictive and analytical models, and translating business and operational requirements into scalable AI/ML solutions.

The ideal candidate should have strong fundamentals in machine learning, Python, data processing, model development, and deployment, along with an interest in applying AI to manufacturing, industrial automation, and operational optimization.

Key Responsibilities

• Design, develop, train, and evaluate machine learning models for industrial and manufacturing use cases.
• Analyze large and complex datasets to identify patterns, trends, anomalies, and opportunities for optimization.
• Perform data preprocessing, feature engineering, model selection, and performance evaluation.
• Develop solutions for use cases such as predictive maintenance, anomaly detection, quality prediction, process optimization, forecasting, and equipment monitoring.
• Work with structured and time-series data generated from industrial equipment, machines, sensors, and operational systems.
• Develop and optimize ML pipelines for data preparation, model training, validation, and deployment.
• Collaborate with domain experts, data engineers, software engineers, and business stakeholders to understand requirements and translate them into technical solutions.
• Deploy machine learning models into production environments and monitor model performance.
• Troubleshoot model and data-related issues and continuously improve model accuracy, reliability, and scalability.
• Develop reusable code, APIs, and components to integrate ML models with enterprise and industrial applications.
• Document models, methodologies, experiments, results, and technical implementations.
• Stay updated with emerging AI/ML techniques, industrial AI trends, and smart manufacturing technologies.

Required Technical Skills

• Strong programming experience in Python.
• Good understanding of Machine Learning algorithms and concepts.
• Experience with libraries/frameworks such as Scikit-learn, Pandas, NumPy, and preferably TensorFlow or PyTorch.
• Strong understanding of data preprocessing, feature engineering, model training, validation, and evaluation.
• Experience working with time-series data is preferred.
• Good understanding of statistical concepts and data analysis.
• Experience with SQL and relational databases.
• Understanding of model deployment and productionization of ML solutions.
• Familiarity with Git and software development best practices.
• Good problem-solving and analytical skills.

Preferred Skills

• Experience in Industrial AI, Smart Manufacturing, Industry 4.0, or Industrial IoT (IIoT).
• Experience with predictive maintenance, anomaly detection, forecasting, or quality inspection.
• Exposure to sensor data, machine/equipment data, telemetry, or real-time industrial data.
• Knowledge of computer vision for manufacturing or quality inspection use cases.
• Exposure to cloud platforms such as AWS, Azure, or GCP.
• Familiarity with Docker, Kubernetes, or CI/CD for ML deployment.
• Knowledge of MLOps concepts and tools.
• Exposure to Generative AI/LLMs is an added advantage. 

Data Engineer Hiring Post

🚨 Hiring: Data Engineer | PySpark + Python + SQL

We are looking for experienced Data Engineers to join our team!

🔹 Experience: 5 to 9 Years

🔹 Locations: Bangalore / Hyderabad

🔹 Interview Process:

• 1st Round – Virtual

• 2nd Round – Face-to-Face (Karat Test)

🔑 Key Skills:

✅ PySpark

✅ SQL

✅ Python

✅ ETL

📩 Interested candidates can share their updated resume.

#Hiring #DataEngineer #PySpark #Python #SQL #ETL #BangaloreJobs #HyderabadJobs #TechHiring #ImmediateHiring

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!