Data Engineer and Data Bricks

Data Engineer 

Mandatory Requirements  

• Experience in AWS Glue 

• Experience in Apache Parquet  
• Proficient in AWS S3 and data lake  
• Knowledge of Snowflake 
• Understanding of file-based ingestion best practices. 
• Scripting language - Python & pyspark 

CORE RESPONSIBILITIES 

• Create and manage cloud resources in AWS  
• Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, REST HTTP API, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies  
• Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform  

• Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations  
• Develop an infrastructure to collect, transform, combine and publish/distribute customer data. 
• Define process improvement opportunities to optimize data collection, insights and displays. 
• Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible  
• Identify and interpret trends and patterns from complex data sets  

• Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders.  
• Key participant in regular Scrum ceremonies with the agile teams   
• Proficient at developing queries, writing reports and presenting findings  
• Mentor junior members and bring best industry practices  

QUALIFICATIONS 

• 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales)  
• Strong background in math, statistics, computer science, data science or related discipline 
• Advanced knowledge one of language: Java, Scala, Python, C#  
• Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake   

• Proficient with 
• Data mining/programming tools (e.g. SAS, SQL, R, Python) 
• Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum) 
• Data visualization (e.g. Tableau, Looker, MicroStrategy) 
• Comfortable learning about and deploying new technologies and tools.  

• Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines.  
• Good written and oral communication skills and ability to present results to non-technical audiences  
• Knowledge of business intelligence and analytical tools, technologies and techniques. 

Familiarity and experience in the following is a plus:  

• AWS certification 
• Spark Streaming  
• Kafka Streaming / Kafka Connect  
• ELK Stack  
• Cassandra / MongoDB  

• CI/CD: Jenkins, GitLab, Jira, Confluence other related tools 

Requirements:

• 2+ years of experience (4+ for Senior Data Engineer) with system/data integration, development or implementation of enterprise and/or cloud software Engineering degree in Computer Science, Engineering or related field.
• Extensive hands-on experience with data integration/EAI technologies (File, API, Queues, Streams), ETL Tools and building custom data pipelines.
• Demonstrated proficiency with Python, JavaScript and/or Java
• Familiarity with version control/SCM is a must (experience with git is a plus).
• Experience with relational and NoSQL databases (any vendor) Solid understanding of cloud computing concepts.
• Strong organisational and troubleshooting skills with attention to detail.
• Strong analytical ability, judgment and problem-solving techniques Interpersonal and communication skills with the ability to work effectively in a cross functional team.

Skills and requirements

• Experience analyzing complex and varied data in a commercial or academic setting.
• Desire to solve new and complex problems every day.
• Excellent ability to communicate scientific results to both technical and non-technical team members.

Desirable

• A degree in a numerically focused discipline such as, Maths, Physics, Chemistry, Engineering or Biological Sciences..
• Hands on experience on Python, Pyspark, SQL
• Hands on experience on building End to End Data Pipelines.
• Hands on Experience on Azure Data Factory, Azure Data Bricks, Data Lake - added advantage
• Hands on Experience in building data pipelines.
• Experience with Bigdata Tools, Hadoop, Hive, Sqoop, Spark, SparkSQL
• Experience with SQL or NoSQL databases for the purposes of data retrieval and management.
• Experience in data warehousing and business intelligence tools, techniques and technology, as well as experience in diving deep on data analysis or technical issues to come up with effective solutions.
• BS degree in math, statistics, computer science or equivalent technical field.
• Experience in data mining structured and unstructured data (SQL, ETL, data warehouse, Machine Learning etc.) in a business environment with large-scale, complex data sets.
• Proven ability to look at solutions in unconventional ways. Sees opportunities to innovate and can lead the way.
• Willing to learn and work on Data Science, ML, AI.

JOB DESCRIPTION:. THE IDEAL CANDIDATE WILL:

• Ensure new features and subject areas are modelled to integrate with existing structures and provide a consistent view. Develop and maintain documentation of the data architecture, data flow and data models of the data warehouse appropriate for various audiences. Provide direction on adoption of Cloud technologies (Snowflake) and industry best practices in the field of data warehouse architecture and modelling.

• Providing technical leadership to large enterprise scale projects. You will also be responsible for preparing estimates and defining technical solutions to proposals (RFPs). This role requires a broad range of skills and the ability to step into different roles depending on the size and scope of the project Roles & Responsibilities.

ELIGIBILITY CRITERIA: Desired Experience/Skills:
• Must have total 5+ yrs. in IT and 2+ years' experience working as a snowflake Data Architect and 4+ years in Data warehouse, ETL, BI projects.
• Must have experience at least two end to end implementation of Snowflake cloud data warehouse and 3 end to end data warehouse implementations on-premise preferably on Oracle.

• Expertise in Snowflake – data modelling, ELT using Snowflake SQL, implementing complex stored Procedures and standard DWH and ETL concepts
• Expertise in Snowflake advanced concepts like setting up resource monitors, RBAC controls, virtual warehouse sizing, query performance tuning, Zero copy clone, time travel and understand how to use these features
• Expertise in deploying Snowflake features such as data sharing, events and lake-house patterns
• Hands-on experience with Snowflake utilities, SnowSQL, SnowPipe, Big Data model techniques using Python
• Experience in Data Migration from RDBMS to Snowflake cloud data warehouse
• Deep understanding of relational as well as NoSQL data stores, methods and approaches (star and snowflake, dimensional modelling)
• Experience with data security and data access controls and design
• Experience with AWS or Azure data storage and management technologies such as S3 and ADLS
• Build processes supporting data transformation, data structures, metadata, dependency and workload management
• Proficiency in RDBMS, complex SQL, PL/SQL, Unix Shell Scripting, performance tuning and troubleshoot
• Provide resolution to an extensive range of complicated data pipeline related problems, proactively and as issues surface
• Must have expertise in AWS or Azure Platform as a Service (PAAS)
• Certified Snowflake cloud data warehouse Architect (Desirable)
• Should be able to troubleshoot problems across infrastructure, platform and application domains.
• Must have experience of Agile development methodologies
• Strong written communication skills. Is effective and persuasive in both written and oral communication

Nice to have Skills/Qualifications:Bachelor's and/or master’s degree in computer science or equivalent experience.
• Strong communication, analytical and problem-solving skills with a high attention to detail.

About you:
• You are self-motivated, collaborative, eager to learn, and hands on
• You love trying out new apps, and find yourself coming up with ideas to improve them
• You stay ahead with all the latest trends and technologies
• You are particular about following industry best practices and have high standards regarding quality

Job Description:

We are looking for a Big Data Engineer who have worked across the entire ETL stack. Someone who has ingested data in a batch and live stream format, transformed large volumes of daily and built Data-warehouse to store the transformed data and has integrated different visualization dashboards and applications with the data stores.    The primary focus will be on choosing optimal solutions to use for these purposes, then maintaining, implementing, and monitoring them.

Responsibilities:

• Develop, test, and implement data solutions based on functional / non-functional business requirements.
• You would be required to code in Scala and PySpark daily on Cloud as well as on-prem infrastructure
• Build Data Models to store the data in a most optimized manner
• Identify, design, and implement process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Implementing the ETL process and optimal data pipeline architecture
• Monitoring performance and advising any necessary infrastructure changes.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.
• Proactively identify potential production issues and recommend and implement solutions
• Must be able to write quality code and build secure, highly available systems.
• Create design documents that describe the functionality, capacity, architecture, and process.
• Review peer-codes and pipelines before deploying to Production for optimization issues and code standards

Skill Sets:

• Good understanding of optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and ‘big data’ technologies.
• Proficient understanding of distributed computing principles
• Experience in working with batch processing/ real-time systems using various open-source technologies like NoSQL, Spark, Pig, Hive, Apache Airflow.
• Implemented complex projects dealing with the considerable data size (PB).
• Optimization techniques (performance, scalability, monitoring, etc.)
• Experience with integration of data from multiple data sources
• Experience with NoSQL databases, such as HBase, Cassandra, MongoDB, etc.,
• Knowledge of various ETL techniques and frameworks, such as Flume
• Experience with various messaging systems, such as Kafka or RabbitMQ
• Creation of DAGs for data engineering
• Expert at Python /Scala programming, especially for data engineering/ ETL purposes

• Collaborate with the business teams to understand the data environment in the organization; develop and lead the Data Scientists team to test and scale new algorithms through pilots and subsequent scaling up of the solutions
• Influence, build and maintain the large-scale data infrastructure required for the AI projects, and integrate with external IT infrastructure/service
• Act as the single point source for all data related queries; strong understanding of internal and external data sources; provide inputs in deciding data-schemas
• Design, develop and maintain the framework for the analytics solutions pipeline
• Provide inputs to the organization’s initiatives on data quality and help implement frameworks and tools for the various related initiatives
• Work in cross-functional teams of software/machine learning engineers, data scientists, product managers, and others to build the AI ecosystem
• Collaborate with the external organizations including vendors, where required, in respect of all data-related queries as well as implementation initiatives

About us

SteelEye is the only regulatory compliance technology and data analytics firm that offers transaction reporting, record keeping, trade reconstruction, best execution and data insight in one comprehensive solution. The firm’s scalable secure data storage platform offers encryption at rest and in flight and best-in-class analytics to help financial firms meet regulatory obligations and gain competitive advantage.

The company has a highly experienced management team and a strong board, who have decades of technology and management experience and worked in senior positions at many leading international financial businesses. We are a young company that shares a commitment to learning, being smart, working hard and being honest in all we do and striving to do that better each day. We value all our colleagues equally and everyone should feel able to speak up, propose an idea, point out a mistake and feel safe, happy and be themselves at work.

Being part of a start-up can be equally exciting as it is challenging. You will be part of the SteelEye team not just because of your talent but also because of your entrepreneurial flare which we thrive on at SteelEye. This means we want you to be curious, contribute, ask questions and share ideas. We encourage you to get involved in helping shape our business. What you'll do

What you will do?

• Deliver plugins for our python based ETL pipelines.
• Deliver python services for provisioning and managing cloud infrastructure.
• Design, Develop, Unit Test, and Support code in production.
• Deal with challenges associated with large volumes of data.
• Manage expectations with internal stakeholders and context switch between multiple deliverables as priorities change.
• Thrive in an environment that uses AWS and Elasticsearch extensively.
• Keep abreast of technology and contribute to the evolution of the product.
• Champion best practices and provide mentorship.

What we're looking for

• Python 3.
• Python libraries used for data (such as pandas, numpy).
• AWS.
• Elasticsearch.
• Performance tuning.
• Object Oriented Design and Modelling.
• Delivering complex software, ideally in a FinTech setting.
• CI/CD tools.
• Knowledge of design patterns.
• Sharp analytical and problem-solving skills.
• Strong sense of ownership.
• Demonstrable desire to learn and grow.
• Excellent written and oral communication skills.
• Mature collaboration and mentoring abilities.

What will you get?

• This is an individual contributor role. So, if you are someone who loves to code and solve complex problems and build amazing products and not worry about anything else, this is the role for you.
• You will have the chance to learn from the best in the business who have worked across the world and are technology geeks.
• Company that always appreciates ownership and initiative. If you are someone who is full of ideas, this role is for you.

• Does analytics to extract insights from raw historical data of the organization. 
• Generates usable training dataset for any/all MV projects with the help of Annotators, if needed.
• Analyses user trends, and identifies their biggest bottlenecks in Hammoq Workflow.
• Tests the short/long term impact of productized MV models on those trends.
• Skills - Numpy, Pandas, SPARK, APACHE SPARK, PYSPARK, ETL mandatory.