krtrimaiq cognitive solutions
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Jobs at krtrimaiq cognitive solutions
Job Description:
Job Title: Informatica Data Quality Engineer!
📍 Location: Bangalore (Hybrid)
💼 Experience: 3+ Years
🕒 Type: Full-Time | Immediate Joiners Preferred
About Us:
At KrtrimaIQ Cognitive Solutions, we build cutting-edge AI & data management systems that empower enterprises to make smarter, data-driven decisions. Join our mission to transform enterprise data intelligence!
Role Overview:
We’re looking for an Informatica Data Quality Engineer (IDQ) to ensure data accuracy, consistency, and compliance across applications. You’ll design, develop, and optimize data quality solutions and collaborate closely with data architects and analysts.
What You’ll Do:
✨ Design & deploy Informatica IDQ solutions (profiling, cleansing, matching, validation)
⚙️ Support ETL/data integration using Informatica PowerCenter or similar tools
📊 Build & maintain data quality scorecards and performance metrics
🧠 Conduct data audits, resolve issues, and document transformation logic
Requirements:
✅ 2+ years of hands-on experience in Informatica IDQ
✅ Strong SQL & data integration knowledge
✅ Excellent problem-solving & analytical skills
✅ Experience with ETL / data governance frameworks
Nice to Have:
⭐ Informatica IDQ / PowerCenter Certification
⭐ Knowledge of AWS / Azure / Big Data tools
Interview Mode:
🚶♂️ Walk-In / Face-to-Face (Bangalore) — Must be open to attend in-person interviews
💻 Remote options may be considered post-onboarding
Perks & Benefits:
💰 Competitive pay & performance bonuses
💡 Learning & growth opportunities
🏡 Hybrid & flexible work options
📩 Interested?
Send your resume to 📧 [your email ID]
📝 Subject line: Application – Informatica Data Quality Engineer
#Hiring #InformaticaIDQ #DataQualityEngineer #ETL #DataGovernance #PowerCenter #SQL #DataEngineering #AIJobs #HybridJobs #BangaloreJobs #KrtrimaIQ #NowHiring #JobAlert #CareerOpportunity
Machine Learning (ML)Job description
We are looking for a Data Scientist with strong AI/ML engineering skills to join our high-impact team at KrtrimaIQ Cognitive Solutions. This is not a notebook-only role — you must have production-grade experience deploying and scaling AI/ML models in cloud environments, especially GCP, AWS, or Azure.
This role involves building, training, deploying, and maintaining ML models at scale, integrating them with business applications. Basic model prototyping won't qualify — we’re seeking hands-on expertise in building scalable machine learning pipelines.
Key Responsibilities
Design, train, test, and deploy end-to-end ML models on GCP (or AWS/Azure) to support product innovation and intelligent automation.
Implement GenAI use cases using LLMs
Perform complex data mining and apply statistical algorithms and ML techniques to derive actionable insights from large datasets.
Drive the development of scalable frameworks for automated insight generation, predictive modeling, and recommendation systems.
Work on impactful AI/ML use cases in Search & Personalization, SEO Optimization, Marketing Analytics, Supply Chain Forecasting, and Customer Experience.
Implement real-time model deployment and monitoring using tools like Kubeflow, Vertex AI, Airflow, PySpark, etc.
Collaborate with business and engineering teams to frame problems, identify data sources, build pipelines, and ensure production-readiness.
Maintain deep expertise in cloud ML architecture, model scalability, and performance tuning.
Stay up to date with AI trends, LLM integration, and modern practices in machine learning and deep learning.
Technical Skills Required Core ML & AI Skills (Must-Have):
Strong hands-on ML engineering (70% of the role) — supervised/unsupervised learning, clustering, regression, optimization.
Experience with real-world model deployment and scaling, not just notebooks or prototypes.
Good understanding of ML Ops, model lifecycle, and pipeline orchestration.
Strong with Python 3, Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Seaborn, Matplotlib, etc.
SQL proficiency and experience querying large datasets.
Deep understanding of linear algebra, probability/statistics, Big-O, and scientific experimentation.
Cloud experience in GCP (preferred), AWS, or Azure.
Cloud & Big Data Stack
Hands-on experience with:
GCP tools – Vertex AI, Kubeflow, BigQuery, GCS
Or equivalent AWS/Azure ML stacks
Familiar with Airflow, PySpark, or other pipeline orchestration tools.
Experience reading/writing data from/to cloud services.
Qualifications
Bachelor's/Master’s/Ph.D. in Computer Science, Mathematics, Engineering, Data Science, Statistics, or related quantitative field.
4+ years of experience in data analytics and machine learning roles.
2+ years of experience in Python or similar programming languages (Java, Scala, Rust).
Must have experience deploying and scaling ML models in production.
Nice to Have
Experience with LLM fine-tuning, Graph Algorithms, or custom deep learning architectures.
Background in academic research to production applications.
Building APIs and monitoring production ML models.
Familiarity with advanced math – Graph Theory, PDEs, Optimization Theory.
Communication & Collaboration
Strong ability to explain complex models and insights to both technical and non-technical stakeholders.
Ask the right questions, clarify objectives, and align analytics with business goals.
Comfortable working cross-functionally in agile and collaborative teams.
Important Note:
This is a Data Science-heavy role — 70% of responsibilities involve building, training, deploying, and scaling AI/ML models.
Cloud experience is mandatory (GCP preferred, AWS/Azure acceptable).
Only candidates with hands-on experience in deploying ML models into production (not just notebooks) will be considered.
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