Company Overview: At Codvo, software and people transformations go hand-in-hand. We are a global empathy led technology services company. Product innovation and mature software engineering are part of our core DNA. Respect, Fairness, Growth, Agility, and Inclusiveness are the core values that we aspire to live by each day. We continue to expand our digital strategy, design, architecture, and product management capabilities to offer expertise, outside-the-box thinking, and measurable results. Position Summary We're seeking a highly skilled Sr. Data Engineer to join our team and play a crucial role in delivering cutting-edge data-driven solutions for our clients. The ideal candidate will possess a deep understanding of data engineering principles, proficiency in Python, AWS, Salesforce, SQL, ETL processes, and data warehousing. You'll collaborate directly with clients, translating their business needs into robust, scalable analytics solutions. Key Responsibilities Data Integration and Transformation: Design and implement ETL pipelines to extract, transform, and load data from various sources, including Salesforce, AWS Connect, and other relevant platforms. Integrate historical reporting data across platforms to provide a unified view for analysis. Optimize data ingestion and replication methods for efficient transfer into the data warehouse. Utilize Data Build Tool (DBT) for data transformation and modelling tasks. Ensure data integrity, quality, and security throughout the data lifecycle. Software Engineering: Strong knowledge and hands-on experience of APIs, SDKs, scripting, Web Services, Internet architecture and SQL. Follow established Codvo software development lifecycle (SDLC) methodologies and promote best practices for backend and data engineering. Participate in code reviews to ensure code quality, readability, and maintainability. Design and develop robust APIs and SDKs (if applicable) for seamless data integration and access. Demonstrate strong scripting skills (Python, Shell scripting, etc.) to automate processes and workflows. Data Warehousing and Architecture: Architect, Implement and maintain robust data warehouse solutions leveraging AWS technologies. Ensure data integrity, security, and scalability of the data infrastructure. Collaborate with data scientists and analysts to design data models that support business intelligence and advanced analytics. Einstein Analytics and Einstein Discovery: Develop compelling Einstein Discovery models to optimize agent utilization within Salesforce environments. Implement machine learning (ML) models to enhance customer recommendations and deliver personalized experiences. Design and build insightful visualizations and dashboards using Einstein Analytics to uncover actionable business insights. Collaboration and Teamwork Collaborate closely with data scientists, analysts, and software engineers to design and implement end-to-end data solutions. Effectively communicate technical concepts and updates to other team members. Participate in code reviews and knowledge-sharing sessions to promote best practices within the data engineering team. Agile and Scrum Collaboration: Work within agile development methodologies, including Scrum, to deliver iterative data solutions. Participate regularly in sprint planning, daily standups, and retrospectives to ensure project alignment and continuous improvement. Qualifications Bachelor's degree/BE in computer science, Data Science, Engineering, or a related field; master's degree preferred. 5+ years of hands-on experience as a Data Engineer, with a proven track record of building and managing data pipelines and data warehouses. Must-Have Skills: Advanced proficiency in Python for data manipulation and ETL development. In-depth knowledge of AWS services (S3, EC2, Redshift, Glue, kinesis, Lambda). Extensive experience with Salesforce data structures and API integration. Strong SQL skills and experience designing and optimizing relational databases. Expertise in relational databases (MSSQL/MySQL/Postgres) Strong understanding of data modelling, data warehousing, and data integration concepts. Experience with building and deploying machine learning models in production environments. Understanding of web services (REST, SOAP) and Internet architecture principles. Highly Desirable: Experience with dbt (data build tool) Experience with Einstein Analytics and Einstein Discovery. Familiarity with machine learning concepts and techniques. Experience working within Agile and Scrum frameworks. Familiarity with Scrum artifacts such as product backlog, sprint backlog, and burndown charts. Additional Attributes: Excellent problem-solving and analytical abilities. Strong communication and interpersonal skills. Self-driven, proactive, and adaptable to evolving project requirements. Team-oriented mindset and ability to thrive in a collaborative environment. Experience: 5+ Years Location: Remote Shift timings: 2:30PM to 11:30PM IST