Basic Qualifications
- Need to have a working knowledge of AWS Redshift.
- Minimum 1 year of designing and implementing a fully operational production-grade large-scale data solution on Snowflake Data Warehouse.
- 3 years of hands-on experience with building productized data ingestion and processing pipelines using Spark, Scala, Python
- 2 years of hands-on experience designing and implementing production-grade data warehousing solutions
- Expertise and excellent understanding of Snowflake Internals and integration of Snowflake with other data processing and reporting technologies
- Excellent presentation and communication skills, both written and verbal
- Ability to problem-solve and architect in an environment with unclear requirements
About Marktine
Marktine is a company that specializes in decision science and assists organizations in successfully using data that is being underutilized to make difficult business decisions. The most distinguishing quality of data is the fact that it carries with it a diverse range of challenges and opportunities, even for businesses operating within the same sector. Since the company's inception, Marktine has collaborated with a wide range of businesses and market sectors. The company is continuing to grow, and its long-term goal is to provide data assessment and management services of the highest international caliber.
When seen from the perspective of the team, it ensures compliance with all industry standards, promotes a good work-life balance among workers and leaves opportunity for the expansion of knowledge. The company values collaboration among employees and adheres to a culture that values creativity, transparency, and honesty.
Similar jobs
Senior Software Engineer - Data
Job Description:
We are looking for a tech savvy Data Engineer to join our growing data team. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software developers, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. The hire must be self-directed and comfortable supporting the data needs of multiple teams, systems and products.
Data Engineer Job Responsibilities:
- Develop and maintain scalable data pipelines and build out new API integrations to support continuing increases in data volume and complexity.
- Implement processes and systems to monitor data accuracy, ensuring 100% data availability for key stakeholders and business processes that depend on it.
- Write unit/integration tests and document work.
- Perform data analysis required to troubleshoot data related issues and assist in the resolution of data issues.
- Design data integrations and reporting framework.
- Work with stakeholders including the Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs
- Design and evaluate open source and vendor tools for data lineage.
- Work closely with all business units and engineering teams to develop strategy for long term data platform architecture.
Data Engineer Qualifications / Skills:
- 3+ years of Java development experience
- Experience with or knowledge of Agile Software Development methodologies
- Excellent problem solving and troubleshooting skills
- Process oriented with great documentation skills
- Experience with big data technologies like Kafka, BigQuery, etc
- Experience with AWS cloud services: EC2, RDS, etc
- Experience with message queuing, stream-processing systems
Education, Experience and Licensing Requirements:
- Degree in Computer Science, IT, or similar field; a Master’s is a plus
- 3+ years of hands on development experience
- 3+ years of SQL experience (No-SQL experience is a plus)
- 3+ years of experience with schema design and dimensional data modeling
- Experience designing, building and maintaining data processing systems
• S/he possesses a wide exposure to complete lifecycle of data starting from creation to consumption
• S/he has in the past built repeatable tools / data-models to solve specific business problems
• S/he should have hand-on experience of having worked on projects (either as a consultant or with in a company) that needed them to
o Provide consultation to senior client personnel o Implement and enhance data warehouses or data lakes.
o Worked with business teams or was a part of the team that implemented process re-engineering driven by data analytics/insights
• Should have deep appreciation of how data can be used in decision-making
• Should have perspective on newer ways of solving business problems. E.g. external data, innovative techniques, newer technology
• S/he must have a solution-creation mindset.
Ability to design and enhance scalable data platforms to address the business need
• Working experience on data engineering tool for one or more cloud platforms -Snowflake, AWS/Azure/GCP
• Engage with technology teams from Tredence and Clients to create last mile connectivity of the solutions
o Should have experience of working with technology teams
• Demonstrated ability in thought leadership – Articles/White Papers/Interviews
Mandatory Skills Program Management, Data Warehouse, Data Lake, Analytics, Cloud Platform
Technical Knowledge (Must Have)
- Strong experience in SQL / HiveQL/ AWS Athena,
- Strong expertise in the development of data pipelines (snaplogic is preferred).
- Design, Development, Deployment and administration of data processing applications.
- Good Exposure towards AWS and Azure Cloud computing environments.
- Knowledge around BigData, AWS Cloud Architecture, Best practices, Securities, Governance, Metadata Management, Data Quality etc.
- Data extraction through various firm sources (RDBMS, Unstructured Data Sources) and load to datalake with all best practices.
- Knowledge in Python
- Good knowledge in NoSQL technologies (Neo4J/ MongoDB)
- Experience/knowledge in SnapLogic (ETL Technologies)
- Working knowledge on Unix (AIX, Linux), shell scripting
- Experience/knowledge in Data Modeling. Database Development
- Experience/knowledge creation of reports and dashboards in Tableau/ PowerBI
Job Responsibilities:-
- Develop robust, scalable and maintainable machine learning models to answer business problems against large data sets.
- Build methods for document clustering, topic modeling, text classification, named entity recognition, sentiment analysis, and POS tagging.
- Perform elements of data cleaning, feature selection and feature engineering and organize experiments in conjunction with best practices.
- Benchmark, apply, and test algorithms against success metrics. Interpret the results in terms of relating those metrics to the business process.
- Work with development teams to ensure models can be implemented as part of a delivered solution replicable across many clients.
- Knowledge of Machine Learning, NLP, Document Classification, Topic Modeling and Information Extraction with a proven track record of applying them to real problems.
- Experience working with big data systems and big data concepts.
- Ability to provide clear and concise communication both with other technical teams and non-technical domain specialists.
- Strong team player; ability to provide both a strong individual contribution but also work as a team and contribute to wider goals is a must in this dynamic environment.
- Experience with noisy and/or unstructured textual data.
knowledge graph and NLP including summarization, topic modelling etc
- Strong coding ability with statistical analysis tools in Python or R, and general software development skills (source code management, debugging, testing, deployment, etc.)
- Working knowledge of various text mining algorithms and their use-cases such as keyword extraction, PLSA, LDA, HMM, CRF, deep learning & recurrent ANN, word2vec/doc2vec, Bayesian modeling.
- Strong understanding of text pre-processing and normalization techniques, such as tokenization,
- POS tagging and parsing and how they work at a low level.
- Excellent problem solving skills.
- Strong verbal and written communication skills
- Masters or higher in data mining or machine learning; or equivalent practical analytics / modelling experience
- Practical experience in using NLP related techniques and algorithms
- Experience in open source coding and communities desirable.
Able to containerize Models and associated modules and work in a Microservices environment
Technical/Core skills
- Minimum 3 yrs of exp in Informatica Big data Developer(BDM) in Hadoop environment.
- Have knowledge of informatica Power exchange (PWX).
- Minimum 3 yrs of exp in big data querying tool like Hive and Impala.
- Ability to designing/development of complex mappings using informatica Big data Developer.
- Create and manage Informatica power exchange and CDC real time implementation
- Strong Unix knowledge skills for writing shell scripts and troubleshoot of existing scripts.
- Good knowledge of big data platforms and its framework.
- Good to have an experience in cloudera data platform (CDP)
- Experience with building stream processing systems using Kafka and spark
- Excellent SQL knowledge
Soft skills :
- Ability to work independently
- Strong analytical and problem solving skills
- Attitude of learning new technology
- Regular interaction with vendors, partners and stakeholders
- 6+ months of proven experience as a Data Scientist or Data Analyst
- Understanding of machine-learning and operations research
- Extensive knowledge of R, SQL and Excel
- Analytical mind and business acumen
- Strong Statistical understanding
- Problem-solving aptitude
- BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred
Tiger Analytics is a global AI & analytics consulting firm. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modeled around expertise and mutual respect with a team first mindset. Working at Tiger, you’ll be at the heart of this AI revolution. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire.
We are headquartered in the Silicon Valley and have our delivery centres across the globe. The below role is for our Chennai or Bangalore office, or you can choose to work remotely.
About the Role:
As an Associate Director - Data Science at Tiger Analytics, you will lead data science aspects of endto-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and client interaction.
• Work closely with internal teams and client stakeholders to design analytical approaches to
solve business problems
• Develop and enhance a broad range of cutting-edge data analytics and machine learning
problems across a variety of industries.
• Work on various aspects of the ML ecosystem – model building, ML pipelines, logging &
versioning, documentation, scaling, deployment, monitoring and maintenance etc.
• Lead a team of data scientists and engineers to embed AI and analytics into the client
business decision processes.
Desired Skills:
• High level of proficiency in a structured programming language, e.g. Python, R.
• Experience designing data science solutions to business problems
• Deep understanding of ML algorithms for common use cases in both structured and
unstructured data ecosystems.
• Comfortable with large scale data processing and distributed computing
• Excellent written and verbal communication skills
• 10+ years exp of which 8 years of relevant data science experience including hands-on
programming.
Designation will be commensurate with expertise/experience. Compensation packages among the best in the industry.
Responsibilities
- Build and mentor the computer vision team at TransPacks
- Drive to productionize algorithms (industrial level) developed through hard-core research
- Own the design, development, testing, deployment, and craftsmanship of the team’s infrastructure and systems capable of handling massive amounts of requests with high reliability and scalability
- Leverage the deep and broad technical expertise to mentor engineers and provide leadership on resolving complex technology issues
- Entrepreneurial and out-of-box thinking essential for a technology startup
- Guide the team for unit-test code for robustness, including edge cases, usability, and general reliability
Eligibility
- Tech in Computer Science and Engineering/Electronics/Electrical Engineering, with demonstrated interest in Image Processing/Computer vision (courses, projects etc) and 6-8 years of experience
- Tech in Computer Science and Engineering/Electronics/Electrical Engineering, with demonstrated interest in Image Processing/Computer vision (Thesis work) and 4-7 years of experience
- D in Computer Science and Engineering/Electronics/Electrical Engineering, with demonstrated interest in Image Processing/Computer vision (Ph. D. Dissertation) and inclination to working in Industry to provide innovative solutions to practical problems
Requirements
- In-depth understanding of image processing algorithms, pattern recognition methods, and rule-based classifiers
- Experience in feature extraction, object recognition and tracking, image registration, noise reduction, image calibration, and correction
- Ability to understand, optimize and debug imaging algorithms
- Understating and experience in openCV library
- Fundamental understanding of mathematical techniques involved in ML and DL schemas (Instance-based methods, Boosting methods, PGM, Neural Networks etc.)
- Thorough understanding of state-of-the-art DL concepts (Sequence modeling, Attention, Convolution etc.) along with knack to imagine new schemas that work for the given data.
- Understanding of engineering principles and a clear understanding of data structures and algorithms
- Experience in writing production level codes using either C++ or Java
- Experience with technologies/libraries such as python pandas, numpy, scipy
- Experience with tensorflow and scikit.
Mining large volumes of credit behavior data to generate insights around product holdings and monetization opportunities for cross sell
Use data science to size opportunity and product potential for launch of any new product/pilots
Build propensity models using heuristics and campaign performance to maximize efficiency.
Conduct portfolio analysis and establish key metrics for cross sell partnership
Desired profile/Skills:
2-5 years of experience with a degree in any quantitative discipline such as Engineering, Computer Science, Economics, Statistics or Mathematics
Excellent problem solving and comprehensive analytical skills – ability to structure ambiguous problem statements, perform detailed analysis and derive crisp insights.
Solid experience in using python and SQL
Prior work experience in a financial services space would be highly valued
Location: Bangalore/ Ahmedabad