6+ Snow flake schema Jobs in Chennai | Snow flake schema Job openings in Chennai

Greetings!!!!

We are looking for a data engineer for one of our premium clients for their Chennai and Tirunelveli location

Required Education/Experience

● Bachelor’s degree in computer Science or related field

● 5-7 years’ experience in the following:

● Snowflake, Databricks management,

● Python and AWS Lambda

● Scala and/or Java

● Data integration service, SQL and Extract Transform Load (ELT)

● Azure or AWS for development and deployment

● Jira or similar tool during SDLC

● Experience managing codebase using Code repository in Git/GitHub or Bitbucket

● Experience working with a data warehouse.

● Familiarity with structured and semi-structured data formats including JSON, Avro, ORC, Parquet, or XML

● Exposure to working in an agile work environment

Job Location: Hyderabad/Bangalore/ Chennai/Pune/Nagpur

Notice period: Immediate - 15 days

1.      Python Developer with Snowflake

Job Description :

1. 5.5+ years of Strong Python Development Experience with Snowflake.
2. Strong hands of experience with SQL ability to write complex queries.
3. Strong understanding of how to connect to Snowflake using Python, should be able to handle any type of files
4.  Development of Data Analysis, Data Processing engines using Python
5. Good Experience in Data Transformation using Python. 
6.  Experience in Snowflake data load using Python.
7.  Experience in creating user-defined functions in Snowflake.
8.  Snowsql implementation.
9.  Knowledge of query performance tuning will be added advantage.
10. Good understanding of Datawarehouse (DWH) concepts.
11.  Interpret/analyze business requirements & functional specification
12.  Good to have DBT, FiveTran, and AWS Knowledge.

Striim (pronounced “stream” with two i’s for integration and intelligence) was founded in 2012 with a simple goal of helping companies make data useful the instant it’s born.

Striim’s enterprise-grade, streaming integration with intelligence platform makes it easy to build continuous, streaming data pipelines – including change data capture (CDC) – to power real-time cloud integration, log correlation, edge processing, and streaming analytics.

Strong Core Java / C++ experience

·       Excellent understanding of Logical ,Object-oriented design patterns, algorithms and data structures.

·       Sound knowledge of application access methods including authentication mechanisms, API quota limits, as well as different endpoint REST, Java etc

·       Strong exp in databases - not just a SQL Programmer but with knowledge of DB internals

·       Sound knowledge of Cloud database available as service is plus (RDS, CloudSQL, Google BigQuery, Snowflake )

·       Experience working in any cloud environment and microservices based architecture utilizing GCP, Kubernetes, Docker, CircleCI, Azure or similar technologies

·       Experience in Application verticals such as ERP, CRM, Sales with applications such as Salesforce, Workday, SAP  < Not Mandatory - added advantage >

·       Experience in building distributed systems  < Not Mandatory - added advantage >

·       Expertise on Data warehouse < Not Mandatory - added advantage >

·       Exp in developing & delivering product as SaaS i< Not Mandatory - added advantage 

We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.

Skills:

- 5+ years deploying Machine Learning pipelines in large enterprise production systems.

- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.

Roles and Responsibilities:

Deploying ML models into production, and scaling them to serve millions of customers.

Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.

Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.

Provide software design and programming support to projects.

 Qualifications & Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.