12 Erstudio Jobs

This role at Weekday's client requires a talented and experienced Senior Data Modeler to join the team. As a Senior Data Modeler, you will play a crucial role in designing, implementing, and maintaining data models that enhance data quality, performance, and scalability. Your responsibilities will involve collaborating with various teams, including data analysts, architects, and business stakeholders, to ensure that the data models align with business requirements and facilitate efficient data management. Key Responsibilities: - Design, implement, and maintain data models that support business requirements, focusing on high data quality, performance, and scalability. - Collaborate with data analysts, data architects, and business stakeholders to ensure alignment of data models with business needs. - Utilize expertise in Azure, Databricks, and data warehousing to develop and manage data solutions. - Manage and optimize relational and NoSQL databases such as Teradata, SQL Server, Oracle, MySQL, MongoDB, and Cassandra. - Contribute to enhancing ETL processes and data integration pipelines for seamless data flows. - Apply data modeling principles and techniques like ERD and UML to create effective data models. - Stay updated with industry trends and emerging technologies, including big data technologies like Hadoop and Spark. - Develop and maintain data models using tools such as ER/Studio and Hackolade. - Drive the adoption of best practices and standards for data modeling within the organization. Skills and Qualifications: - Minimum of 6+ years of experience in data modeling, with a track record of implementing scalable and efficient data models. - Proficiency in Azure and Databricks for building data solutions. - Strong understanding of data modeling principles and techniques such as ERD and UML. - Experience with relational databases (e.g., Teradata, SQL Server, Oracle, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra). - Solid knowledge of data warehousing, ETL processes, and data integration. - Familiarity with big data technologies like Hadoop and Spark is advantageous. - Industry Knowledge: Background in supply chain is preferred but not mandatory. - Excellent analytical and problem-solving skills. - Strong communication skills to engage with technical and non-technical stakeholders effectively. - Ability to thrive in a collaborative, fast-paced environment.,

You will be responsible for designing and implementing logical and physical data models to meet application requirements. This includes developing and maintaining relational database structures using SQL Server. You will create and optimize stored procedures, views, functions, and triggers to ensure data integrity, consistency, and scalability. Performance tuning, query optimization, and indexing strategies will be within your scope, along with analyzing execution plans and troubleshooting slow-running queries. Collaboration with developers, analysts, and DevOps teams is essential to deliver high-performing solutions. Furthermore, you will maintain and enhance existing database systems while adhering to best practices and security standards. To excel in this role, you should possess 6-10 years of hands-on experience with Microsoft SQL Server. A strong background in data modeling, including ER diagrams, normalization, and schema design, is required. You must have in-depth knowledge of T-SQL and database development best practices. Experience in database performance tuning, index design, and execution plan analysis is crucial. Proficiency in database design tools such as ER/Studio, ERwin, or Visio is expected, along with familiarity with version control and CI/CD practices for database changes. Desirable skills include experience with SSIS, SSRS, or Power BI, as well as exposure to cloud database platforms like Azure SQL or AWS RDS. Possessing Microsoft certifications in SQL Server technologies would be an added advantage.,

As a Data Engineering Lead, you will be responsible for developing and implementing data engineering projects, including enterprise data hubs or Big data platforms. Your role will involve defining reference data architecture, leveraging cloud-native data platforms in AWS or Microsoft stack, and staying updated on the latest data trends like data fabric and data mesh. You will play a key role in leading the Center of Excellence (COE) and influencing client revenues through innovative data and analytics solutions. Your responsibilities will include guiding a team of data engineers, overseeing the design and deployment of data solutions, and strategizing new data services and offerings. Collaborating with client teams to understand their business challenges, you will develop tailored data solutions and lead client engagements from project initiation to deployment. Building strong relationships with key clients and stakeholders, you will also create reusable methodologies, pipelines, and models for more efficient data science projects. Your expertise in data architecture solutions, data governance, and data modeling will ensure compliance with regulatory standards and support effective data management processes. You will be proficient in various data integration tools, cloud computing platforms, programming languages, data visualization tools, and big data technologies to process and analyze large volumes of data. In addition to technical skills, you will demonstrate strong people and interpersonal skills by managing a high-performing team, fostering a culture of innovation, and collaborating with cross-functional teams. Candidates for this role should have at least 10+ years of experience in information technology, with a focus on data engineering and architecture, along with a degree in relevant fields like computer science, data science, or engineering. Candidates should also possess experience in managing data projects, creating data and analytics solutions, and have a good understanding of data visualization, reporting tools, and normalizing data as per key KPIs and metrics. Strong problem-solving, communication, and collaboration skills are essential for success in this role.,

You are a talented and experienced Senior Data Modeler who will be responsible for designing, implementing, and maintaining data models to enhance data quality, performance, and scalability. Your role will involve collaborating with cross-functional teams, including data analysts, architects, and business stakeholders, to ensure that the data models align with business requirements and drive efficient data management. Your key responsibilities will include designing, implementing, and maintaining data models that support business requirements, collaborating with various teams to align data models with business needs, leveraging expertise in Azure, Databricks, and data warehousing, managing and optimizing relational and NoSQL databases, contributing to ETL processes and data integration pipelines, applying data modeling principles and techniques, staying updated with industry trends and emerging technologies, and driving the adoption of best practices for data modeling within the organization. To excel in this role, you should have a minimum of 6+ years of experience in data modeling, expertise in Azure and Databricks, proficiency in data modeling tools like ER/Studio and Hackolade, a strong understanding of data modeling principles and techniques, experience with relational and NoSQL databases, knowledge of data warehousing, ETL processes, and data integration, familiarity with big data technologies like Hadoop and Spark, and excellent analytical and problem-solving skills. Industry knowledge in supply chain is preferred but not mandatory. Additionally, you should have strong communication skills to interact effectively with technical and non-technical stakeholders and the ability to work well in a collaborative, fast-paced environment.,

You should have familiarity with modern storage formats like Parquet and ORC. Your responsibilities will include designing and developing conceptual, logical, and physical data models to support enterprise data initiatives. You will build, maintain, and optimize data models within Databricks Unity Catalog, developing efficient data structures using Delta Lake to optimize performance, scalability, and reusability. Collaboration with data engineers, architects, analysts, and stakeholders is essential to ensure data model alignment with ingestion pipelines and business goals. You will translate business and reporting requirements into a robust data architecture using best practices in data warehousing and Lakehouse design. Additionally, maintaining comprehensive metadata artifacts such as data dictionaries, data lineage, and modeling documentation is crucial. Enforcing and supporting data governance, data quality, and security protocols across data ecosystems will be part of your role. You will continuously evaluate and improve modeling processes. The ideal candidate will have 10+ years of hands-on experience in data modeling in Big Data environments. Expertise in OLTP, OLAP, dimensional modeling, and enterprise data warehouse practices is required. Proficiency in modeling methodologies including Kimball, Inmon, and Data Vault is expected. Hands-on experience with modeling tools like ER/Studio, ERwin, PowerDesigner, SQLDBM, dbt, or Lucidchart is preferred. Proven experience in Databricks with Unity Catalog and Delta Lake is necessary, along with a strong command of SQL and Apache Spark for querying and transformation. Experience with the Azure Data Platform, including Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL Database is beneficial. Exposure to Azure Purview or similar data cataloging tools is a plus. Strong communication and documentation skills are required, with the ability to work in cross-functional agile environments. Qualifications for this role include a Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related field. Certifications such as Microsoft DP-203: Data Engineering on Microsoft Azure are desirable. Experience working in agile/scrum environments and exposure to enterprise data security and regulatory compliance frameworks (e.g., GDPR, HIPAA) are also advantageous.,

As a Data Modeler, you will be responsible for developing and maintaining conceptual, logical, and physical data models along with their corresponding metadata. Your role will involve performing data mapping based on data source schemas and reverse engineering existing transformations from multiple source database systems on a cloud data platform to align with corporate standards. Additionally, you will conduct data analysis, capture data requirements, and collaborate with squad members and product owners to implement data strategies effectively. One of your key responsibilities will be to validate logical data models with business subject matter experts and work closely with the development team to ensure that all requirements are captured and reflected in the data model. You will also collaborate with the DBA team to design physical models that optimize performance. Active participation in metadata definition and management will be essential in this role. To excel in this position, you should be proficient in data modeling techniques using tools such as Erwin, ER/Studio, and Power Designer. A willingness to learn and strong communication skills are also important attributes for success in this role. If you have 6 to 9 years of experience, you can expect a salary of 18 L, while candidates with 9 to 12 years of experience can anticipate a salary of 24 L. This is an excellent opportunity to leverage your skills and expertise as a Data Modeler to contribute to the success of the organization.,

Data Modeler -SA Role Overview We are looking for an experienced Data Modeler with a strong foundation in dimensional data modeling and a proven ability to design and maintain conceptual, logical, and physical data models. The ideal candidate will have a minimum of 5+ years of experience in data modeling and architecture, preferably within the banking or financial services industry. Key Responsibilities Design, develop, and maintain dimensional data models to support analytics and reporting. Design conceptual, logical, and physical data models Utilize AWS services for scalable data model design Align data models with business rules and governance standards. Collaborate with business stakeholders, data architects, and engineers to ensure data models align with business rules and data governance standards. Translate business requirements into scalable and efficient data models. Maintain comprehensive documentation for data models, metadata, and data dictionaries. Ensure consistency and integrity of data models across systems and platforms. Partner with data engineering teams to implement models in AWS-based environments, including Redshift, Glue, and Lake Formation. Required Skills and Qualifications 5+ years of experience in data modeling, with a focus on dimensional modeling and data warehouse design. Proficiency in developing conceptual, logical, and physical data models. Strong understanding of data governance, data quality, and metadata management. Hands-on experience with AWS services such as Redshift, Glue, and Lake Formation. Familiarity with data modeling tools (e.g., ER/Studio, ERwin, or similar). Excellent communication skills and ability to work with cross-functional teams. Preferred Qualifications Experience in the banking or financial services sector. Knowledge of data lake architecture and modern data stack tools. AWS or data modeling certifications are a plus.

You are a versatile Data Model Developer with 6 to 9 years of experience, proficient in designing robust data models across cloud (GCP) and traditional RDBMS environments. Your role involves collaborating with cross-functional teams to develop schemas that cater to both operational systems and analytical use cases. Your key responsibilities include designing and implementing scalable data models for cloud (GCP) and traditional RDBMS, supporting hybrid data architectures integrating real-time and batch workflows, collaborating with engineering teams for seamless schema implementation, documenting conceptual, logical, and physical models, assisting in ETL and data pipeline alignment with schema definitions, and monitoring and refining performance through partitioning and indexing strategies. You must have experience with GCP data services like BigQuery, CloudSQL, AlloyDB, proficiency in relational databases such as PostgreSQL, MySQL, or Oracle, solid grounding in OLTP/OLAP modeling principles, familiarity with schema design tools like DBSchema, ER/Studio, and SQL expertise for query performance optimization. Preferred skills include experience working in hybrid cloud/on-prem data architectures, functional knowledge in BFSI or asset management domains, and knowledge of metadata management and schema versioning. Soft skills required for this role include adaptability to cloud and legacy tech stacks, clear communication with engineers and analysts, and strong documentation and collaboration skills. Joining this role will allow you to contribute to dual-mode data architecture (cloud + on-prem), solve real-world data design challenges in regulated industries, and have the opportunity to influence platform migration and modernization.,

As a Functional Data Modeler in the Mutual Fund industry, you will play a vital role in designing data models that accurately represent fund structures, NAV calculations, asset allocation, and compliance workflows. Your expertise in data modeling, combined with a deep understanding of mutual funds and BFSI domains, will be instrumental in creating schemas that meet operational and regulatory requirements. Your responsibilities will include collaborating with business analysts and product teams to translate functional requirements into effective data structures. It will be crucial for you to ensure that the data models you design comply with data privacy regulations, regulatory reporting standards, and audit requirements. Additionally, you will be responsible for building OLTP and OLAP data models to support real-time and aggregated reporting needs and documenting metadata, lineage, and data dictionaries for business use. To excel in this role, you must have a strong domain expertise in Mutual Fund/BFSI operations and a proven track record in data modeling for financial and regulatory systems. Proficiency in schema design on GCP platforms such as BigQuery and CloudSQL, as well as hands-on experience with modeling tools like DBSchema or ER/Studio, are essential skills required for this position. Preferred skills for this role include experience working with fund management platforms or reconciliation engines and familiarity with financial compliance standards such as SEBI and FATCA. Soft skills like strong business acumen and effective documentation capabilities will also be valuable in liaising between functional and technical teams successfully. By joining our team, you will have the opportunity to own critical financial data architecture, influence domain-driven modeling for financial ecosystems, and be part of a fast-paced data transformation journey in the BFSI sector. If you are looking to make a significant impact in the field of data modeling within the mutual fund industry, this role is perfect for you.,

The Data Warehouse Engineer will be responsible for managing and optimizing data processes in an Azure environment using Snowflake. The ideal candidate should have solid SQL skills and a basic understanding of data modeling. Experience with CI/CD processes and Azure ADF is preferred. Additionally, expertise in ETL/ELT frameworks and ER/Studio would be a plus. As a Senior Data Warehouse Engineer, in addition to the core requirements, you will oversee other engineers while also being actively involved in data modeling and Snowflake SQL optimization. You will be responsible for conducting design reviews, code reviews, and deployment reviews with the engineering team. Familiarity with medallion architecture and experience in Healthcare or life sciences industry will be highly advantageous. At Myridius, we are committed to transforming the way businesses operate by offering tailored solutions in AI, data analytics, digital engineering, and cloud innovation. With over 50 years of expertise, we aim to drive organizations through the rapidly evolving landscapes of technology and business. Our integration of cutting-edge technology with deep domain knowledge enables businesses to seize new opportunities, drive significant growth, and maintain a competitive edge in the global market. We go beyond typical service delivery to craft transformative outcomes that help businesses not just adapt, but thrive in a world of continuous change. Discover how Myridius can elevate your business to new heights of innovation by visiting us at www.myridius.com and start leading the change.,

As a Data Warehouse Engineer at Myridius, you will be responsible for working with solid SQL language skills and possessing basic knowledge of data modeling. Your role will involve collaborating with Snowflake in Azure, CI/CD process using any tooling. Additionally, familiarity with Azure ADF and ETL/ELT frameworks would be beneficial for this position. It would be advantageous to have experience in ER/Studio and a good understanding of Healthcare/life sciences industry. Knowledge of GxP processes will be a plus in this role. For a Senior Data Warehouse Engineer position, you will be overseeing engineers while actively engaging in the same tasks. Your responsibilities will include conducting design reviews, code reviews, and deployment reviews with engineers. You should have expertise in solid data modeling, preferably using ER/Studio or an equivalent tool. Optimizing Snowflake SQL queries to enhance performance and familiarity with medallion architecture will be key aspects of this role. At Myridius, we are dedicated to transforming the way businesses operate by offering tailored solutions in AI, data analytics, digital engineering, and cloud innovation. With over 50 years of expertise, we drive a new vision to propel organizations through rapidly evolving technology and business landscapes. Our commitment to exceeding expectations ensures measurable impact and fosters sustainable innovation. Together with our clients, we co-create solutions that anticipate future trends and help businesses thrive in a world of continuous change. If you are passionate about driving significant growth and maintaining a competitive edge in the global market, join Myridius in crafting transformative outcomes and elevating businesses to new heights of innovation. Visit www.myridius.com to learn more about how we lead the change.,

As a Data Model Designer, you will be responsible for structuring and organizing data to support scalable applications and reporting systems. Your role will play a crucial part in maintaining data consistency and reusability throughout the organization. Your key responsibilities will include developing and maintaining conceptual, logical, and physical data models, ensuring that these models align with reporting, analytics, and application requirements. You will collaborate with stakeholders to gather data requirements, normalize data, optimize relationships, and work closely with developers and DBAs to implement these models in production. To be successful in this role, you should have 6-9 years of experience in data modeling or business intelligence, a strong understanding of relational databases and data warehousing, and proficiency in data modeling tools such as PowerDesigner, dbt, and ER/Studio. You should possess the ability to interpret business needs and translate them into effective data structures, with a keen attention to detail. It would be advantageous if you have experience with dimensional modeling, including star/snowflake schemas, and familiarity with master data management concepts. Key Skills: er/studio, data warehousing, modeling, powerdesigner, relational databases, data modeling tools, business intelligence, master data management, data, dimensional modeling, dbt, data modeling,