Data Engineering

at MathCo

Data Engineering

MathCo

Company

Home

Data Engineering

at MathCo

Posted by Nabhan Mustafa

2 - 8 yrs

Best in industry

Bengaluru (Bangalore)

Skills

Data Warehouse (DWH)

Microsoft Windows Azure

Data engineering

Python

Amazon Web Services (AWS)

ETL

Spark

Responsible for designing, storing, processing, and maintaining of large-scale data and related infrastructure.
Can drive multiple projects both from operational and technical standpoint.
Ideate and build PoV or PoC for new product that can help drive more business.
Responsible for defining, designing, and implementing data engineering best practices, strategies, and solutions.
Is an Architect who can guide the customers, team, and overall organization on tools, technologies, and best practices around data engineering.
Lead architecture discussions, align with business needs, security, and best practices.
Has strong conceptual understanding of Data Warehousing and ETL, Data Governance and Security, Cloud Computing, and Batch & Real Time data processing
Has strong execution knowledge of Data Modeling, Databases in general (SQL and NoSQL), software development lifecycle and practices, unit testing, functional programming, etc.
Understanding of Medallion architecture pattern
Has worked on at least one cloud platform.
Has worked as data architect and executed multiple end-end data engineering project.
Has extensive knowledge of different data architecture designs and data modelling concepts.
Manages conversation with the client stakeholders to understand the requirement and translate it into technical outcomes.

Required Tech Stack

Strong proficiency in SQL
Experience working on any of the three major cloud platforms i.e., AWS/Azure/GCP
Working knowledge of an ETL and/or orchestration tools like IICS, Talend, Matillion, Airflow, Azure Data Factory, AWS Glue, GCP Composer, etc.
Working knowledge of one or more OLTP databases (Postgres, MySQL, SQL Server, etc.)
Working knowledge of one or more Data Warehouse like Snowflake, Redshift, Azure Synapse, Hive, Big Query, etc.
Proficient in at least one programming language used in data engineering, such as Python (or Scala/Rust/Java)
Has strong execution knowledge of Data Modeling (star schema, snowflake schema, fact vs dimension tables)
Proficient in Spark and related applications like Databricks, GCP DataProc, AWS Glue, EMR, etc.
Has worked on Kafka and real-time streaming.
Has strong execution knowledge of data architecture design patterns (lambda vs kappa architecture, data harmonization, customer data platforms, etc.)
Has worked on code and SQL query optimization.
Strong knowledge of version control systems like Git to manage source code repositories and designing CI/CD pipelines for continuous delivery.
Has worked on data and networking security (RBAC, secret management, key vaults, vnets, subnets, certificates)

Responsible for designing, storing, processing, and maintaining of large-scale data and related infrastructure.
Can drive multiple projects both from operational and technical standpoint.
Ideate and build PoV or PoC for new product that can help drive more business.
Responsible for defining, designing, and implementing data engineering best practices, strategies, and solutions.
Is an Architect who can guide the customers, team, and overall organization on tools, technologies, and best practices around data engineering.
Lead architecture discussions, align with business needs, security, and best practices.
Has strong conceptual understanding of Data Warehousing and ETL, Data Governance and Security, Cloud Computing, and Batch & Real Time data processing
Has strong execution knowledge of Data Modeling, Databases in general (SQL and NoSQL), software development lifecycle and practices, unit testing, functional programming, etc.
Understanding of Medallion architecture pattern
Has worked on at least one cloud platform.
Has worked as data architect and executed multiple end-end data engineering project.
Has extensive knowledge of different data architecture designs and data modelling concepts.
Manages conversation with the client stakeholders to understand the requirement and translate it into technical outcomes.

Required Tech Stack

Strong proficiency in SQL
Experience working on any of the three major cloud platforms i.e., AWS/Azure/GCP
Working knowledge of an ETL and/or orchestration tools like IICS, Talend, Matillion, Airflow, Azure Data Factory, AWS Glue, GCP Composer, etc.
Working knowledge of one or more OLTP databases (Postgres, MySQL, SQL Server, etc.)
Working knowledge of one or more Data Warehouse like Snowflake, Redshift, Azure Synapse, Hive, Big Query, etc.
Proficient in at least one programming language used in data engineering, such as Python (or Scala/Rust/Java)
Has strong execution knowledge of Data Modeling (star schema, snowflake schema, fact vs dimension tables)
Proficient in Spark and related applications like Databricks, GCP DataProc, AWS Glue, EMR, etc.
Has worked on Kafka and real-time streaming.
Has strong execution knowledge of data architecture design patterns (lambda vs kappa architecture, data harmonization, customer data platforms, etc.)
Has worked on code and SQL query optimization.
Strong knowledge of version control systems like Git to manage source code repositories and designing CI/CD pipelines for continuous delivery.
Has worked on data and networking security (RBAC, secret management, key vaults, vnets, subnets, certificates)

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About MathCo

Founded

Type

Size

Stage

About

TheMathCompany or MathCo® is a global Enterprise AI and Analytics company, trusted for data-driven decision making by some of the largest organizations across industries. Founded in 2016, MathCo builds custom data products through its innovative hybrid model and transfers the ownership of intellectual properties to its clients. NucliOS, MathCo's proprietary platform with pre-built workflows and reusable plug-and-play modules, enables the vision of connected intelligence at a lower TCO. MathCo's full-stack team provides a holistic range of services spanning strategy, advanced analytics, data engineering and governance, MLOps, GenAI, data visualization, and adoption advisory services. MathCo's numerous accolades include recognitions in Gartner's Magic Quadrant for D&A Providers, Everest Group's Peak Matrix Assessment, and being listed as a Great Place to Work. To know more about how MathCo supports organizations to own and activate intelligence, visit our website.

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