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Job Title: Data Engineer

Job Summary: As a Data Engineer, you will be responsible for designing, building, and maintaining the infrastructure and tools necessary for data collection, storage, processing, and analysis. You will work closely with data scientists and analysts to ensure that data is available, accessible, and in a format that can be easily consumed for business insights.

Responsibilities:

• Design, build, and maintain data pipelines to collect, store, and process data from various sources.
• Create and manage data warehousing and data lake solutions.
• Develop and maintain data processing and data integration tools.
• Collaborate with data scientists and analysts to design and implement data models and algorithms for data analysis.
• Optimize and scale existing data infrastructure to ensure it meets the needs of the business.
• Ensure data quality and integrity across all data sources.
• Develop and implement best practices for data governance, security, and privacy.
• Monitor data pipeline performance / Errors and troubleshoot issues as needed.
• Stay up-to-date with emerging data technologies and best practices.

Requirements:

Bachelor's degree in Computer Science, Information Systems, or a related field.

Experience with ETL tools like Matillion,SSIS,Informatica

Experience with SQL and relational databases such as SQL server, MySQL, PostgreSQL, or Oracle.

Experience in writing complex SQL queries

Strong programming skills in languages such as Python, Java, or Scala.

Experience with data modeling, data warehousing, and data integration.

Strong problem-solving skills and ability to work independently.

Excellent communication and collaboration skills.

Familiarity with big data technologies such as Hadoop, Spark, or Kafka.

Familiarity with data warehouse/Data lake technologies like Snowflake or Databricks

Familiarity with cloud computing platforms such as AWS, Azure, or GCP.

Familiarity with Reporting tools

Teamwork/ growth contribution

• Helping the team in taking the Interviews and identifying right candidates
• Adhering to timelines
• Intime status communication and upfront communication of any risks
• Tech, train, share knowledge with peers.
• Good Communication skills
• Proven abilities to take initiative and be innovative
• Analytical mind with a problem-solving aptitude

Good to have :

Master's degree in Computer Science, Information Systems, or a related field.

Experience with NoSQL databases such as MongoDB or Cassandra.

Familiarity with data visualization and business intelligence tools such as Tableau or Power BI.

Knowledge of machine learning and statistical modeling techniques.

If you are passionate about data and want to work with a dynamic team of data scientists and analysts, we encourage you to apply for this position.

• Expertise in designing and implementing enterprise scale database (OLTP) and Data warehouse solutions.
• Hands on experience in implementing Azure SQL Database, Azure SQL Date warehouse (Azure Synapse Analytics) and big data processing using Azure Databricks and Azure HD Insight.
• Expert in writing T-SQL programming for complex stored procedures, functions, views and query optimization.
• Should be aware of Database development for both on-premise and SAAS Applications using SQL Server and PostgreSQL.
• Experience in ETL and ELT implementations using Azure Data Factory V2 and SSIS.
• Experience and expertise in building machine learning models using Logistic and linear regression, Decision tree  and Random forest Algorithms.
• PolyBase queries for exporting and importing data into Azure Data Lake.
• Building data models both tabular and multidimensional using SQL Server data tools.
• Writing data preparation, cleaning and processing steps using Python, SCALA, and R.
• Programming experience using python libraries NumPy, Pandas and Matplotlib.
• Implementing NOSQL databases and writing queries using cypher.
• Designing end user visualizations using Power BI, QlikView and Tableau.
• Experience working with all versions of SQL Server 2005/2008/2008R2/2012/2014/2016/2017/2019
• Experience using the expression languages MDX and DAX.
• Experience in migrating on-premise SQL server database to Microsoft Azure.
• Hands on experience in using Azure blob storage, Azure Data Lake Storage Gen1 and Azure Data Lake Storage Gen2.
• Performance tuning complex SQL queries, hands on experience using SQL Extended events.
• Data modeling using Power BI for Adhoc reporting.
• Raw data load automation using T-SQL and SSIS
• Expert in migrating existing on-premise database to SQL Azure.
• Experience in using U-SQL for Azure Data Lake Analytics.
• Hands on experience in generating SSRS reports using MDX.
• Experience in designing predictive models using Python and SQL Server.
• Developing machine learning models using Azure Databricks and SQL Server