AWS Data Engineer
Barclays · Pune Division, Maharashtra, India
- On site
- Full-time
- $120,000 / year
- Pune Division, Maharashtra, India
Job highlights
- Build and maintain AWS data pipelines and warehouses.
- Develop data solutions using Python, PySpark, and Snowflake.
- Ensure data accuracy, accessibility, and security.
- Collaborate on innovation and digital landscape evolution.
- Work on Location Strategy projects in Pune.
About the role
AWS Data Engineer - Location Strategy Projects
Barclays is seeking an experienced AWS Data Engineer to support the successful delivery of Location Strategy projects. This role is crucial in shaping our digital landscape, driving innovation, and ensuring unparalleled customer experiences by leveraging cutting-edge technology.
Key Responsibilities
- Support the delivery of Location Strategy projects, adhering to agreed quality and governance standards.
- Spearhead the evolution of the digital landscape, driving innovation and excellence.
- Utilize cutting-edge technology to revolutionize digital offerings and enhance customer experiences.
- Build and maintain systems for data collection, storage, processing, and analysis, including data pipelines, data warehouses, and data lakes.
- Ensure data accuracy, accessibility, and security.
- Design and implement scalable and efficient data transformation/storage solutions.
- Develop processing and analysis algorithms for complex data scenarios.
- Collaborate with data scientists to build and deploy machine learning models.
Technical Skills & Experience Required
- Hands-on experience with Python and PySpark, including strong knowledge of DataFrames, RDD, and SparkSQL.
- Hands-on experience developing, testing, and maintaining applications on AWS Cloud.
- Strong proficiency in AWS Data Analytics Technology Stack: Glue, S3, Lambda, Lake Formation, Athena.
- Experience designing and implementing scalable and efficient data transformation/storage solutions using Snowflake.
- Experience with data ingestion into Snowflake for various formats (Parquet, Iceberg, JSON, CSV, etc.).
- Experience using DBT (Data Build Tool) with Snowflake for ELT pipeline development.
- Experience writing advanced SQL and PL/SQL programs.
- Experience in AWS data pipeline development.
- Hands-on experience building reusable components using Snowflake and AWS Tools/Technology.
- Proven experience in at least two major project implementations.
Advantageous Skills
- Exposure to data governance or lineage tools (e.g., Immuta, Alation).
- Experience with orchestration tools (e.g., Apache Airflow, Snowflake Tasks).
- Knowledge of Ab Initio ETL tool.
Valued Skills & Competencies
- Ability to engage with stakeholders, elicit requirements, and translate them into ETL components.
- Understanding of infrastructure setup and ability to provide solutions.
- Good knowledge of Data Marts and Data Warehousing concepts.
- Strong analytical and interpersonal skills.
- Experience implementing cloud-based enterprise data warehouses with multiple data platforms (Snowflake, NoSQL) to build data movement strategies.
- Knowledge of risk and controls, change and transformation, business acumen, strategic thinking, and digital/technology.
Purpose of the Role
To build and maintain the systems that collect, store, process, and analyse data, ensuring accuracy, accessibility, and security.
Analyst Expectations
Perform prescribed activities timely and to a high standard, driving continuous improvement. Requires in-depth technical knowledge and experience, with a thorough understanding of underlying principles. For leadership roles, demonstrate LEAD behaviors (Listen, Energise, Align, Develop). For individual contributors, develop technical expertise and act as an advisor. Partner with other functions and business areas, taking responsibility for end results, escalating breaches, and embedding new policies. Advise and influence decision-making, own risk management, and deliver in line with regulations. Maintain understanding of functional integration and organizational objectives.
Barclays Values
All colleagues are expected to demonstrate Barclays Values: Respect, Integrity, Service, Excellence, and Stewardship. Also demonstrate the Barclays Mindset: Empower, Challenge, and Drive.
Key skills/competency
- AWS Data Engineer
- Python
- PySpark
- SparkSQL
- AWS Cloud
- Snowflake
- Data Transformation
- Data Ingestion
- DBT
- SQL
Skills & topics
- AWS Data Engineer
- Data Engineering
- AWS
- Python
- PySpark
- Snowflake
- Data Warehousing
- ETL
- Data Pipelines
- Cloud Data
How to get hired
- Tailor your resume: Highlight AWS, Python, PySpark, Snowflake, and data warehousing skills. Quantify achievements.
- Craft a strong cover letter: Emphasize your understanding of data architecture and stakeholder engagement.
- Prepare for technical interviews: Review SQL, PySpark, AWS services (Glue, S3, Lambda), and data modeling concepts.
- Showcase problem-solving: Be ready to discuss project implementations and challenges overcome.
- Understand Barclays culture: Research their values (Respect, Integrity, Service, Excellence, Stewardship) and mindset (Empower, Challenge, Drive).
Technical preparation
Master Python and PySpark data manipulation.,Deep dive into AWS Glue, S3, Lambda, Lake Formation.,Practice SQL, PL/SQL, and Snowflake query optimization.,Build ELT pipelines with DBT and orchestration tools.
Behavioral questions
Describe a complex data project you led.,How do you handle conflicting stakeholder requirements?,Share an instance of driving continuous improvement.,How do you ensure data quality and security?
Frequently asked questions
- What are the core AWS services used by the AWS Data Engineer at Barclays?
- The core AWS services frequently utilized by an AWS Data Engineer at Barclays include AWS Glue, S3, Lambda, Lake Formation, and Athena, forming the foundation of their data analytics stack.
- What programming languages are essential for this AWS Data Engineer role at Barclays?
- Proficiency in Python and PySpark is essential for this AWS Data Engineer role at Barclays, particularly with experience in DataFrames, RDD, and SparkSQL for data processing and manipulation.
- Does this AWS Data Engineer position at Barclays involve data warehousing and data lakes?
- Yes, this AWS Data Engineer position at Barclays is deeply involved in designing and implementing data warehouses and data lakes to manage data volumes, velocity, and security.
- What role does Snowflake play in this AWS Data Engineer job at Barclays?
- Snowflake is a key technology for this AWS Data Engineer role at Barclays, used for designing and implementing scalable data transformation and storage solutions, as well as data ingestion and ELT pipeline development with DBT.
- Are stakeholder engagement and requirement gathering part of the AWS Data Engineer responsibilities at Barclays?
- Yes, the AWS Data Engineer at Barclays is expected to engage with stakeholders, elicit requirements, and translate them into effective ETL components and data solutions.
- What are the 'LEAD' behaviors mentioned for leadership roles in this AWS Data Engineer position at Barclays?
- For leadership roles, the 'LEAD' behaviors at Barclays are Listen and be authentic, Energise and inspire, Align across the enterprise, and Develop others, fostering a thriving work environment.
- Is experience with data governance tools a requirement for the AWS Data Engineer at Barclays?
- While not a strict requirement, exposure to data governance or lineage tools such as Immuta and Alation is considered an added advantage for the AWS Data Engineer role at Barclays.
- What is the expected technical output for an AWS Data Engineer at Barclays regarding data processing?
- An AWS Data Engineer at Barclays is expected to develop processing and analysis algorithms that are suitable for the intended data complexity and volumes, ensuring efficient and effective data handling.