Senior SQL Developer / Lead

Company Description

UpSolve is a Gen AI and Vision AI startup that helps businesses solve their problems by building custom solutions that drive strategic business decisions. Whether your business is facing time constraints or a lack of resources, UpSolve can help. We build enterprise grade AI solutions with focus on increasing ROI.

Role Description

This is a full-time hybrid role for a Business Analyst located in Mumbai.

Please note: This is an onsite role and good communication skills are expected (oral + written)

Responsibilities

1. Understand existing system integrations for the client.

2. Map and identify gaps in existing systems.

3. Ideate, Advise and Implement AI Solutions to optimize business process.

4. Collaborate with multiple teams and stakeholders.

Qualifications

• MBA with focus on Business Analytics or Bachelor's degree in Computer Science or IT
• Minimum 4 Years of Experience
• Strong written, verbal and collaboration skills
• Immediate Joiner (Less than 5 days)

Work Location: Mumbai, Work from Office

Mandatory Skills: Azure Data Lake Storage, Azure SQL databases, Azure Synapse, Data Bricks (Pyspark/Spark), Python, SQL, Azure Data Factory.

Good to have: Power BI, Azure IAAS services, Azure Devops, Microsoft Fabric

Ø Very strong understanding on ETL and ELT

Ø Very strong understanding on Lakehouse architecture.

Ø Very strong knowledge in Pyspark and Spark architecture.

Ø Good knowledge in Azure data lake architecture and access controls

Ø Good knowledge in Microsoft Fabric architecture

Ø Good knowledge in Azure SQL databases

Ø Good knowledge in T-SQL

Ø Good knowledge in CI /CD process using Azure devops

Ø Power BI

• Core Java: advanced level competency, should have worked on projects with core Java development.

• Linux shell : advanced level competency, work experience with Linux shell scripting, knowledge and experience to use important shell commands

• Rdbms, SQL: advanced level competency, Should have expertise in SQL query language syntax, should be well versed with aggregations, joins of SQL query language.

• Data structures and problem solving: should have ability to use appropriate data structure.

• AWS cloud : Good to have experience with aws serverless toolset along with aws infra

• Data Engineering ecosystem : Good to have experience and knowledge of data engineering, ETL, data warehouse (any toolset)

• Hadoop, HDFS, YARN : Should have introduction to internal working of these toolsets

• HIVE, MapReduce, Spark: Good to have experience developing transformations using hive queries, MapReduce job implementation and Spark Job Implementation. Spark implementation in Scala will be plus point.

• Airflow, Oozie, Sqoop, Zookeeper, Kafka: Good to have knowledge about purpose and working of these technology toolsets. Working experience will be a plus point here.

Job Description:

As an Azure Data Engineer, your role will involve designing, developing, and maintaining data solutions on the Azure platform. You will be responsible for building and optimizing data pipelines, ensuring data quality and reliability, and implementing data processing and transformation logic. Your expertise in Azure Databricks, Python, SQL, Azure Data Factory (ADF), PySpark, and Scala will be essential for performing the following key responsibilities:

Designing and developing data pipelines: You will design and implement scalable and efficient data pipelines using Azure Databricks, PySpark, and Scala. This includes data ingestion, data transformation, and data loading processes.

Data modeling and database design: You will design and implement data models to support efficient data storage, retrieval, and analysis. This may involve working with relational databases, data lakes, or other storage solutions on the Azure platform.

Data integration and orchestration: You will leverage Azure Data Factory (ADF) to orchestrate data integration workflows and manage data movement across various data sources and targets. This includes scheduling and monitoring data pipelines.

Data quality and governance: You will implement data quality checks, validation rules, and data governance processes to ensure data accuracy, consistency, and compliance with relevant regulations and standards.

Performance optimization: You will optimize data pipelines and queries to improve overall system performance and reduce processing time. This may involve tuning SQL queries, optimizing data transformation logic, and leveraging caching techniques.

Monitoring and troubleshooting: You will monitor data pipelines, identify performance bottlenecks, and troubleshoot issues related to data ingestion, processing, and transformation. You will work closely with cross-functional teams to resolve data-related problems.

Documentation and collaboration: You will document data pipelines, data flows, and data transformation processes. You will collaborate with data scientists, analysts, and other stakeholders to understand their data requirements and provide data engineering support.

Skills and Qualifications:

Strong experience with Azure Databricks, Python, SQL, ADF, PySpark, and Scala.

Proficiency in designing and developing data pipelines and ETL processes.

Solid understanding of data modeling concepts and database design principles.

Familiarity with data integration and orchestration using Azure Data Factory.

Knowledge of data quality management and data governance practices.

Experience with performance tuning and optimization of data pipelines.

Strong problem-solving and troubleshooting skills related to data engineering.

Excellent collaboration and communication skills to work effectively in cross-functional teams.

Understanding of cloud computing principles and experience with Azure services.

Title:  Data Engineer – Snowflake

Location: Mysore (Hybrid model)

Exp-2-8 yrs

Type: Full Time

Walk-in date: 25th Jan 2023 @Mysore 

Job Role: We are looking for an experienced Snowflake developer to join our team as a Data Engineer who will work as part of a team to help design and develop data-driven solutions that deliver insights to the business. The ideal candidate is a data pipeline builder and data wrangler who enjoys building data-driven systems that drive analytical solutions and building them from the ground up. You will be responsible for building and optimizing our data as well as building automated processes for production jobs. You will support our software developers, database architects, data analysts and data scientists on data initiatives

Key Roles & Responsibilities:

• Use advanced complex Snowflake/Python and SQL to extract data from source systems for ingestion into a data pipeline.
• Design, develop and deploy scalable and efficient data pipelines.
• Analyze and assemble large, complex datasets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements. For example: automating manual processes, optimizing data delivery, re-designing data platform infrastructure for greater scalability.
• Build required infrastructure for optimal extraction, loading, and transformation (ELT) of data from various data sources using AWS and Snowflake leveraging Python or SQL technologies.
• Monitor cloud-based systems and components for availability, performance, reliability, security and efficiency
• Create and configure appropriate cloud resources to meet the needs of the end users.
• As needed, document topology, processes, and solution architecture.
• Share your passion for staying on top of tech trends, experimenting with and learning new technologies

Qualifications & Experience

Qualification & Experience Requirements:

• Bachelor's degree in computer science, computer engineering, or a related field.
• 2-8 years of experience working with Snowflake
• 2+ years of experience with the AWS services.
• Candidate should able to write the stored procedure and function in Snowflake.
• At least 2 years’ experience in snowflake developer.
• Strong SQL Knowledge.
• Data injection in snowflake using Snowflake procedure.
• ETL Experience is Must (Could be any tool)
• Candidate should be aware of snowflake architecture.
• Worked on the Migration project
• DW Concept (Optional)
• Experience with cloud data storage and compute components including lambda functions, EC2s, containers.
• Experience with data pipeline and workflow management tools: Airflow, etc.
• Experience cleaning, testing, and evaluating data quality from a wide variety of ingestible data sources
• Experience working with Linux and UNIX environments.
• Experience with profiling data, with and without data definition documentation

• Familiar with Git
• Familiar with issue tracking systems like JIRA (Project Management Tool) or Trello.
• Experience working in an agile environment.

Desired Skills:

• Experience in Snowflake. Must be willing to be Snowflake certified in the first 3 months of employment.
• Experience with a stream-processing system: Snowpipe
• Working knowledge of AWS or Azure
• Experience in migrating from on-prem to cloud systems

We are looking for an outstanding Big Data Engineer with experience setting up and maintaining Data Warehouse and Data Lakes for an Organization. This role would closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Roles and Responsibilities:

• Develop and maintain scalable data pipelines and build out new integrations and processes required for optimal extraction, transformation, and loading of data from a wide variety of data sources using 'Big Data' technologies.
• Develop programs in Scala and Python as part of data cleaning and processing.
• Assemble large, complex data sets that meet functional / non-functional business requirements and fostering data-driven decision making across the organization.  
• Responsible to design and develop distributed, high volume, high velocity multi-threaded event processing systems.
• Implement processes and systems to validate data, monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
• Perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Provide high operational excellence guaranteeing high availability and platform stability.
• Closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Skills:

• Experience with Big Data pipeline, Big Data analytics, Data warehousing.
• Experience with SQL/No-SQL, schema design and dimensional data modeling.
• Strong understanding of Hadoop Architecture, HDFS ecosystem and eexperience with Big Data technology stack such as HBase, Hadoop, Hive, MapReduce.
• Experience in designing systems that process structured as well as unstructured data at large scale.
• Experience in AWS/Spark/Java/Scala/Python development.
• Should have Strong skills in PySpark (Python & SPARK). Ability to create, manage and manipulate Spark Dataframes. Expertise in Spark query tuning and performance optimization.
• Experience in developing efficient software code/frameworks for multiple use cases leveraging Python and big data technologies.
• Prior exposure to streaming data sources such as Kafka.
• Should have knowledge on Shell Scripting and Python scripting.
• High proficiency in database skills (e.g., Complex SQL), for data preparation, cleaning, and data wrangling/munging, with the ability to write advanced queries and create stored procedures.
• Experience with NoSQL databases such as Cassandra / MongoDB.
• Solid experience in all phases of Software Development Lifecycle - plan, design, develop, test, release, maintain and support, decommission.
• Experience with DevOps tools (GitHub, Travis CI, and JIRA) and methodologies (Lean, Agile, Scrum, Test Driven Development).
• Experience building and deploying applications on on-premise and cloud-based infrastructure.
• Having a good understanding of machine learning landscape and concepts. 

Qualifications and Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Big Data Engineer or a similar role for 3-5 years.

Certifications:

Good to have at least one of the Certifications listed here:

    AZ 900 - Azure Fundamentals

    DP 200, DP 201, DP 203, AZ 204 - Data Engineering

    AZ 400 - Devops Certification