Azure – Data Engineer
- At least 2 years hands on experience working with an Agile data engineering team working on big data pipelines using Azure in a commercial environment.
- Dealing with senior stakeholders/leadership
- Understanding of Azure data security and encryption best practices. [ADFS/ACLs]
Data Bricks –experience writing in and using data bricks Using Python to transform, manipulate data.
Data Factory – experience using data factory in an enterprise solution to build data pipelines. Experience calling rest APIs.
Synapse/data warehouse – experience using synapse/data warehouse to present data securely and to build & manage data models.
Microsoft SQL server – We’d expect the candidate to have come from a SQL/Data background and progressed into Azure
PowerBI – Experience with this is preferred
Additionally
- Experience using GIT as a source control system
- Understanding of DevOps concepts and application
- Understanding of Azure Cloud costs/management and running platforms efficiently
About Marktine
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Requirements:
● Understanding our data sets and how to bring them together.
● Working with our engineering team to support custom solutions offered to the product development.
● Filling the gap between development, engineering and data ops.
● Creating, maintaining and documenting scripts to support ongoing custom solutions.
● Excellent organizational skills, including attention to precise details
● Strong multitasking skills and ability to work in a fast-paced environment
● 5+ years experience with Python to develop scripts.
● Know your way around RESTFUL APIs.[Able to integrate not necessary to publish]
● You are familiar with pulling and pushing files from SFTP and AWS S3.
● Experience with any Cloud solutions including GCP / AWS / OCI / Azure.
● Familiarity with SQL programming to query and transform data from relational Databases.
● Familiarity to work with Linux (and Linux work environment).
● Excellent written and verbal communication skills
● Extracting, transforming, and loading data into internal databases and Hadoop
● Optimizing our new and existing data pipelines for speed and reliability
● Deploying product build and product improvements
● Documenting and managing multiple repositories of code
● Experience with SQL and NoSQL databases (Casendra, MySQL)
● Hands-on experience in data pipelining and ETL. (Any of these frameworks/tools: Hadoop, BigQuery,
RedShift, Athena)
● Hands-on experience in AirFlow
● Understanding of best practices, common coding patterns and good practices around
● storing, partitioning, warehousing and indexing of data
● Experience in reading the data from Kafka topic (both live stream and offline)
● Experience in PySpark and Data frames
Responsibilities:
You’ll
● Collaborating across an agile team to continuously design, iterate, and develop big data systems.
● Extracting, transforming, and loading data into internal databases.
● Optimizing our new and existing data pipelines for speed and reliability.
● Deploying new products and product improvements.
● Documenting and managing multiple repositories of code.
4 - 8 overall experience.
- 1-2 years’ experience in Azure Data Factory - schedule Jobs in Flows and ADF Pipelines, Performance Tuning, Error logging etc..
- 1+ years of experience with Power BI - designing and developing reports, dashboards, metrics and visualizations in Powe BI.
- (Required) Participate in video conferencing calls - daily stand-up meetings and all day working with team members on cloud migration planning, development, and support.
- Proficiency in relational database concepts & design using star, Azure Datawarehouse, and data vault.
- Requires 2-3 years of experience with SQL scripting (merge, joins, and stored procedures) and best practices.
- Knowledge on deploying and run SSIS packages in Azure.
- Knowledge of Azure Data Bricks.
- Ability to write and execute complex SQL queries and stored procedures.
• Help build a Data Science team which will be engaged in researching, designing,
implementing, and deploying full-stack scalable data analytics vision and machine learning
solutions to challenge various business issues.
• Modelling complex algorithms, discovering insights and identifying business
opportunities through the use of algorithmic, statistical, visualization, and mining techniques
• Translates business requirements into quick prototypes and enable the
development of big data capabilities driving business outcomes
• Responsible for data governance and defining data collection and collation
guidelines.
• Must be able to advice, guide and train other junior data engineers in their job.
Must Have:
• 4+ experience in a leadership role as a Data Scientist
• Preferably from retail, Manufacturing, Healthcare industry(not mandatory)
• Willing to work from scratch and build up a team of Data Scientists
• Open for taking up the challenges with end to end ownership
• Confident with excellent communication skills along with a good decision maker
- Building and operationalizing large scale enterprise data solutions and applications using one or more of AZURE data and analytics services in combination with custom solutions - Azure Synapse/Azure SQL DWH, Azure Data Lake, Azure Blob Storage, Spark, HDInsights, Databricks, CosmosDB, EventHub/IOTHub.
- Experience in migrating on-premise data warehouses to data platforms on AZURE cloud.
- Designing and implementing data engineering, ingestion, and transformation functions
-
Azure Synapse or Azure SQL data warehouse
-
Spark on Azure is available in HD insights and data bricks
- Creating, designing and developing data models
- Prepare plans for all ETL (Extract/Transformation/Load) procedures and architectures
- Validating results and creating business reports
- Monitoring and tuning data loads and queries
- Develop and prepare a schedule for a new data warehouse
- Analyze large databases and recommend appropriate optimization for the same
- Administer all requirements and design various functional specifications for data
- Provide support to the Software Development Life cycle
- Prepare various code designs and ensure efficient implementation of the same
- Evaluate all codes and ensure the quality of all project deliverables
- Monitor data warehouse work and provide subject matter expertise
- Hands-on BI practices, data structures, data modeling, SQL skills
- Minimum 1 year experience in Pyspark
- Actively engage with internal business teams to understand their challenges and deliver robust, data-driven solutions.
- Work alongside global counterparts to solve data-intensive problems using standard analytical frameworks and tools.
- Be encouraged and expected to innovate and be creative in your data analysis, problem-solving, and presentation of solutions.
- Network and collaborate with a broad range of internal business units to define and deliver joint solutions.
- Work alongside customers to leverage cutting-edge technology (machine learning, streaming analytics, and ‘real’ big data) to creatively solve problems and disrupt existing business models.
In this role, we are looking for:
- A problem-solving mindset with the ability to understand business challenges and how to apply your analytics expertise to solve them.
- The unique person who can present complex mathematical solutions in a simple manner that most will understand, including customers.
- An individual excited by innovation and new technology and eager to finds ways to employ these innovations in practice.
- A team mentality, empowered by the ability to work with a diverse set of individuals.
Basic Qualifications
- A Bachelor’s degree in Data Science, Math, Statistics, Computer Science or related field with an emphasis on analytics.
- 5+ Years professional experience in a data scientist/analyst role or similar.
- Proficiency in your statistics/analytics/visualization tool of choice, but preferably in the Microsoft Azure Suite, including Azure ML Studio and PowerBI as well as R, Python, SQL.
Preferred Qualifications
- Excellent communication, organizational transformation, and leadership skills
- Demonstrated excellence in Data Science, Business Analytics and Engineering
bachelor’s degree or equivalent experience
● Knowledge of database fundamentals and fluency in advanced SQL, including concepts
such as windowing functions
● Knowledge of popular scripting languages for data processing such as Python, as well as
familiarity with common frameworks such as Pandas
● Experience building streaming ETL pipelines with tools such as Apache Flink, Apache
Beam, Google Cloud Dataflow, DBT and equivalents
● Experience building batch ETL pipelines with tools such as Apache Airflow, Spark, DBT, or
custom scripts
● Experience working with messaging systems such as Apache Kafka (and hosted
equivalents such as Amazon MSK), Apache Pulsar
● Familiarity with BI applications such as Tableau, Looker, or Superset
● Hands on coding experience in Java or Scala