Data Engineer - SQL, Snowflake

Job description

Job Description Purpose of the role To build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure. Accountabilities Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data. Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures. Development of processing and analysis algorithms fit for the intended data complexity and volumes. Collaboration with data scientist to build and deploy machine learning models. Analyst Expectations To perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement. Requires in-depth technical knowledge and experience in their assigned area of expertise Thorough understanding of the underlying principles and concepts within the area of expertise They lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources. If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others. OR for an individual contributor, they develop technical expertise in work area, acting as an advisor where appropriate. Will have an impact on the work of related teams within the area. Partner with other functions and business areas. Takes responsibility for end results of a team’s operational processing and activities. Escalate breaches of policies / procedure appropriately. Take responsibility for embedding new policies/ procedures adopted due to risk mitigation. Advise and influence decision making within own area of expertise. Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct. Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organisations products, services and processes within the function. Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function. Make evaluative judgements based on the analysis of factual information, paying attention to detail. Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents. Guide and persuade team members and communicate complex / sensitive information. Act as contact point for stakeholders outside of the immediate function, while building a network of contacts outside team and external to the organisation. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave. Join us as a Data Engineer - SQL, Snowflake at Barclays, responsible for supporting the successful delivery of location strategy projects to plan, budget, agreed quality and governance standards. You'll spearhead the evolution of our digital landscape, driving innovation and excellence. You will harness cutting-edge technology to revolutionise our digital offerings, ensuring unparalleled customer experiences. To be successful as a Data Engineer - SQL, Snowflake you should have experience with: SQL – Advanced query writing and performance tuning. Teradata – Experience with enterprise data warehousing. PySpark – Proficiency in distributed data processing. Hadoop – Familiarity with big data tools and architecture. Linux Shell Scripting – Strong scripting skills for automation and data handling. Some other highly valued skills may include: AWS Awareness – Understanding of cloud-based data platforms and services. Prior Exposure to AWS – Experience with data migration or analytics on AWS is a strong plus. You may be assessed on key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen, strategic thinking and digital and technology, as well as job-specific technical skills. This role is based out of Pune.