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A highly experienced software developer and analyst with over 30 years of expertise in employing diverse software development languages, tools, and platforms to enhance, automate, and optimize processes. Demonstrates a proven ability to work effectively both independently and within team environments, think creatively, solve complex challenges, and deliver high-quality solutions. Proficient in full stack development, encompassing both back-end and front-end technologies, with extensive experience in cloud technologies, database management, and data visualization.
I’m a seasoned software and systems engineer with over 20years of experience building reliable, scalable applications in cloud environments like Azure. My work spans full-stack development, infrastructure automation, and system design, with a strong focus on performance, security, and maintainability. I’ve led teams through digital transformations, implemented CI/CD pipelines, and optimized architectures for distributed systems. I’m passionate about continuous learning and enjoy solving complex problems through thoughtful engineering. Outside of work, I freelance, contribute to open-source projects, and mentor aspiring developers.
Senior Data and AI Engineer with 16+ years of experience across data engineering, analytics, and AI/ML. Proven track record in building cloud-native data platforms, implementing GenAI solutions, LLMs, and enterprise-scale RAG pipelines. Expert in Snowflake, AWS, and BI tools like Looker and Tableau. Adept at MLOps, DBT, and AI DevOps for deploying scalable, secure, and intelligent systems. Strong leadership in AI projects, enabling business transformation through automation, data-driven decision-making, and next-gen GenAI applications.
IT Professional with 10+ years of experience in Data Engineering, Machine Learning, and Software Development, specializing in big data processing, ETL pipelines, and predictive analytics. Strong expertise in SQL optimization (Oracle, ClickHouse, SQL Server), Python, PySpark, and cloud platforms (GCP). Proven track record in credit risk modeling, real-time analytics, and high-performance database design. Skilled in automating workflows, building scalable data architectures, and deploying machine learning models to drive business insights. Combines technical proficiency with strategic problem-solving to deliver efficient, data-driven solutions.
I am an interdisciplinary researcher with over 15 years of experience in biomedical informatics, AI, and health data science. My work spans machine learning, natural language processing, and multi-omics integration for clinical and translational research. I have led international teams, published extensively in peer-reviewed journals, and served as an associate editor in top scientific publications. I specialize in developing scalable, data-driven solutions for complex biomedical challenges.
I’m a data scientist and machine learning engineer with 5+ years of experience working on end-to-end ML solutions across industries such as Manufacturing, Energy, Software, among others. My background combines strong statistical analysis, machine learning, and software engineering skills.I’ve built models for predictive analytics, NLP, and computer vision, and have experience deploying them using tools like PyTorch, ONNX, and cloud platforms like GCP & AWS.
I am a data-driven builder with over five years of work in data, AI, and cloud tech. I turn raw input into models, tools, and clear insight for teams and clients. I have strong skill in Python, SQL, and Power BI. I have worked with cloud apps, APIs, and large AI tools to solve real goals in fast setups. I ask the right questions, move with care, and shape each task to fit the need. My focus is always on value, clarity, and trust in the result.
I have a total of 4 years of experience working in Backend with AWS, EKS and Python, Java, Django, Springboot, React JS, etc. I have completed 3 projects, creating a web portal for Splunk and deploying it on EKS. An ETL pipeline for Leap Tools using AWS Glue to provide a scalable and Robust solution. Created integration in OpenTelemetry to collect EKS data for Splunk and enhanced multiple data collectors.
I am a results-driven Data Engineer with over 3 years of experience in building scalable ETL/ELT pipelines, optimizing data workflows, and ensuring data accuracy. Proficient in Python, SQL, and big data tools like Spark and Hive, I specialize in designing and implementing cloud-based data systems using AWS and data orchestration using Apache Airflow/Autosys. My expertise includes data modeling, query optimization, and stream processing. I thrive in collaborative, agile environments and am committed to delivering high-quality, reliable data solutions to support data-driven decision-making.
I’m a Data Analyst and Machine Learning enthusiast with 4+ years of experience in data analytics, dashboard development, and database management. Skilled in Python, SQL, Power BI, and machine learning techniques, I’ve worked on real-world projects involving customer segmentation, predictive modeling, and business intelligence. I value clear communication, remote collaboration, and delivering data-driven insights that help clients make smarter decisions.
At Techamana, we maintain the highest standards in developer selection. Our ETL experts undergo a comprehensive 4-step vetting process that evaluates technical skills, problem-solving abilities, communication skills, and team and culture fit. Only the top 5% of applicants pass our rigorous screening, ensuring you work with exceptional talent who can deliver outstanding results for your projects.
Rigorous coding challenges and problem-solving tests to evaluate ETL proficiency and best practices.
Thorough examination of past projects and contributions to open-source ETL repositories to assess real- world experience.
Video responses for open-ended questions to assess problem-solving ability, communication skills, and team and culture fitment.
When hiring an ETL specialist, prioritize Talend, Informatica, or NiFi experience.
Candidates should design efficient data pipelines, handle cleansing/validation, implement incremental loads, and use Python/SQL scripting for robust workflows.
Industry insights and best practices
ETL (Extract, Transform, Load) processes are used to extract data from various sources, transform it into a usable format, and load it into a target data warehouse or database. Modern ETL tools utilize automation and data quality checks.
ETL processes integrate data from various sources, creating a unified view of data for analysis.
ETL is crucial for loading data into data warehouses, preparing data for analysis and reporting.
ETL processes clean and transform data, ensuring data quality and accuracy.
ETL is used to migrate data from legacy systems to modern data platforms.
Majority of our clients choose to continue working with our talent after their initial project
Our screening and matching process ensures exceptional talent are matched to your precise needs.
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