Cymetrix Software

Bangalore / Chennai

• Hands-on data modelling for OLTP and OLAP systems
• In-depth knowledge of Conceptual, Logical and Physical data modelling
• Strong understanding of Indexing, partitioning, data sharding, with practical experience of having done the same
• Strong understanding of variables impacting database performance for near-real-time reporting and application interaction.
• Should have working experience on at least one data modelling tool, preferably DBSchema, Erwin
• Good understanding of GCP databases like AlloyDB, CloudSQL, and BigQuery.
• People with functional knowledge of the mutual fund industry will be a plus

Role & Responsibilities:

● Work with business users and other stakeholders to understand business processes.

● Ability to design and implement Dimensional and Fact tables

● Identify and implement data transformation/cleansing requirements

● Develop a highly scalable, reliable, and high-performance data processing pipeline to extract, transform and load data from various systems to the Enterprise Data Warehouse

● Develop conceptual, logical, and physical data models with associated metadata including data lineage and technical data definitions

● Design, develop and maintain ETL workflows and mappings using the appropriate data load technique

● Provide research, high-level design, and estimates for data transformation and data integration from source applications to end-user BI solutions.

● Provide production support of ETL processes to ensure timely completion and availability of data in the data warehouse for reporting use.

● Analyze and resolve problems and provide technical assistance as necessary. Partner with the BI team to evaluate, design, develop BI reports and dashboards according to functional specifications while maintaining data integrity and data quality.

● Work collaboratively with key stakeholders to translate business information needs into well-defined data requirements to implement the BI solutions.

● Leverage transactional information, data from ERP, CRM, HRIS applications to model, extract and transform into reporting & analytics.

● Define and document the use of BI through user experience/use cases, prototypes, test, and deploy BI solutions.

● Develop and support data governance processes, analyze data to identify and articulate trends, patterns, outliers, quality issues, and continuously validate reports, dashboards and suggest improvements.

● Train business end-users, IT analysts, and developers.

Required Skills:

● Bachelor’s degree in Computer Science or similar field or equivalent work experience.

● 5+ years of experience on Data Warehousing, Data Engineering or Data Integration projects.

● Expert with data warehousing concepts, strategies, and tools.

● Strong SQL background.

● Strong knowledge of relational databases like SQL Server, PostgreSQL, MySQL.

● Strong experience in GCP & Google BigQuery, Cloud SQL, Composer (Airflow), Dataflow, Dataproc, Cloud Function and GCS

● Good to have knowledge on SQL Server Reporting Services (SSRS), and SQL Server Integration Services (SSIS).

● Knowledge of AWS and Azure Cloud is a plus.

● Experience in Informatica Power exchange for Mainframe, Salesforce, and other new-age data sources.

● Experience in integration using APIs, XML, JSONs etc.

1. GCP - GCS, PubSub, Dataflow or DataProc, Bigquery, BQ optimization, Airflow/Composer, Python(preferred)/Java

2. ETL on GCP Cloud - Build pipelines (Python/Java) + Scripting, Best Practices, Challenges

3. Knowledge of Batch and Streaming data ingestion, build End to Data pipelines on GCP

4. Knowledge of Databases (SQL, NoSQL), On-Premise and On-Cloud, SQL vs No SQL, Types of No-SQL DB (At Least 2 databases)

5. Data Warehouse concepts - Beginner to Intermediate level

6.Data Modeling, GCP Databases, DB Schema(or similar)

7.Hands-on data modelling for OLTP and OLAP systems

8.In-depth knowledge of Conceptual, Logical and Physical data modelling

9.Strong understanding of Indexing, partitioning, data sharding, with practical experience of having done the same

10.Strong understanding of variables impacting database performance for near-real-time reporting and application interaction.

11.Should have working experience on at least one data modelling tool,

preferably DBSchema, Erwin

12Good understanding of GCP databases like AlloyDB, CloudSQL, and

BigQuery.

13.People with functional knowledge of the mutual fund industry will be a plus Should be willing to work from Chennai, office presence is mandatory

Role & Responsibilities:

● Work with business users and other stakeholders to understand business processes.

● Ability to design and implement Dimensional and Fact tables

● Identify and implement data transformation/cleansing requirements

● Develop a highly scalable, reliable, and high-performance data processing pipeline to extract, transform and load data from various systems to the Enterprise Data Warehouse

● Develop conceptual, logical, and physical data models with associated metadata including data lineage and technical data definitions

● Design, develop and maintain ETL workflows and mappings using the appropriate data load technique

● Provide research, high-level design, and estimates for data transformation and data integration from source applications to end-user BI solutions.

● Provide production support of ETL processes to ensure timely completion and availability of data in the data warehouse for reporting use.

● Analyze and resolve problems and provide technical assistance as necessary. Partner with the BI team to evaluate, design, develop BI reports and dashboards according to functional specifications while maintaining data integrity and data quality.

● Work collaboratively with key stakeholders to translate business information needs into well-defined data requirements to implement the BI solutions.

● Leverage transactional information, data from ERP, CRM, HRIS applications to model, extract and transform into reporting & analytics.

● Define and document the use of BI through user experience/use cases, prototypes, test, and deploy BI solutions.

● Develop and support data governance processes, analyze data to identify and articulate trends, patterns, outliers, quality issues, and continuously validate reports, dashboards and suggest improvements.

● Train business end-users, IT analysts, and developers.

Full Stack Developer

Location: Hyderabad

Experience: 7+ Years

Type: BCS - Business Consulting Services

RESPONSIBILITIES:

* Strong programming skills in Node JS [ Must] , React JS, Android and Kotlin [Must]

* Hands on Experience in UI development with good UX sense understanding.  

• Hands on Experience in Database design and management

• Hands on Experience to create and maintain backend-framework for mobile applications.

• Hands-on development experience on cloud-based platforms like GCP/Azure/AWS

• Ability to manage and provide technical guidance to the team.

• Strong experience in designing APIs using RAML, Swagger, etc.  

• Service Definition Development.  

• API Standards, Security, Policies Definition and Management.

REQUIRED EXPERIENCE:

* Bachelor’s and/or master's degree in computer science or equivalent work experience

* Excellent analytical, problem solving, and communication skills.

* 7+ years of software engineering experience in a multi-national company

* 6+ years of development experience in Kotlin, Node and React JS

* 3+ Year(s) experience creating solutions in native public cloud (GCP, AWS or Azure)

* Experience with Git or similar version control system, continuous integration

* Proficiency in automated unit test development practices and design methodologies

* Fluent English

Proficient in Looker Action, Looker Dashboarding, Looker Data Entry, LookML, SQL Queries, BigQuery, LookML, Looker Studio, BigQuery, GCP.



Remote Working

2 pm to 12 am IST or

10:30 AM to 7:30 PM IST

Sunday to Thursday

Responsibilities:

● Create and maintain LookML code, which defines data models, dimensions, measures, and relationships within Looker.

● Develop reusable LookML components to ensure consistency and efficiency in report and dashboard creation.

● Build and customize dashboard to Incorporate data visualizations, such as charts and graphs, to present insights effectively.

● Write complex SQL queries when necessary to extract and manipulate data from underlying databases and also optimize SQL queries for performance.

● Connect Looker to various data sources, including databases, data warehouses, and external APIs.

● Identify and address bottlenecks that affect report and dashboard loading times and Optimize Looker performance by tuning queries, caching strategies, and exploring indexing options.

● Configure user roles and permissions within Looker to control access to sensitive data & Implement data security best practices, including row-level and field-level security.

● Develop custom applications or scripts that interact with Looker's API for automation and integration with other tools and systems.

● Use version control systems (e.g., Git) to manage LookML code changes and collaborate with other developers.

● Provide training and support to business users, helping them navigate and use Looker effectively.

● Diagnose and resolve technical issues related to Looker, data models, and reports.

Skills Required:

● Experience in Looker's modeling language, LookML, including data models, dimensions, and measures.

● Strong SQL skills for writing and optimizing database queries across different SQL databases (GCP/BQ preferable)

● Knowledge of data modeling best practices

● Proficient in BigQuery, billing data analysis, GCP billing, unit costing, and invoicing, with the ability to recommend cost optimization strategies.

● Previous experience in Finops engagements is a plus

● Proficiency in ETL processes for data transformation and preparation.

● Ability to create effective data visualizations and reports using Looker’s dashboard tools.

● Ability to optimize Looker performance by fine-tuning queries, caching strategies, and indexing.

● Familiarity with related tools and technologies, such as data warehousing (e.g., BigQuery ), data transformation tools (e.g., Apache Spark), and scripting languages (e.g., Python).