Senior Data Analytics Engineer

Senior Data Analytics Engineer

Python

You will play a critical role in designing, developing, and maintaining end-to-end data solutions, from building robust data pipelines and models to delivering insightful dashboards and visualizations that empower informed decision-making across the organization and for our clients.

Key Responsibilities:

• Design, build, and maintain robust data pipelines and data models using tools such as Python, Databricks, Azure Data Factory, Snowflake, MS Fabric and MS SQL to ensure accurate, reliable, and scalable data flows from source to dashboard. Work may also involve other modern data platforms and cloud technologies as needed.
• Create dynamic, interactive Power BI dashboards and reports tailored to meet business needs. Ensure visualizations are user-friendly, visually compelling, and deliver meaningful insights for decision-makers.
• Ingest, transform, and model large datasets efficiently. Optimize ETL/ELT workflows, SQL queries, and Power BI data models to deliver high-performance analytics solutions.
• Partner closely with business users and data consumers to gather requirements, define KPIs, and translate business objectives into technical data pipelines and analytical models.
• Continuously monitor and improve data pipeline and dashboard performance. Implement best practices in data validation, quality checks, and system optimization to ensure fast, reliable reporting.
• Maintain comprehensive documentation for data pipelines, models, dashboards, and processes to support transparency, reproducibility, and cross-team collaboration.
• Stay current with the latest developments in data engineering, BI tools, and cloud technologies. Proactively recommend and implement improvements to enhance efficiency and analytical capabilities.

Education:

• Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.

• Experience:

• 5+ years of hands-on experience working across the data lifecycle, including data engineering, modeling, and business intelligence development, whether in a single full-stack role or through multiple complementary positions.
• The ability to

  showcase previous work

  through a

  GitHub repository, portfolio of reports/dashboards

  , or other demonstrable project examples is highly valued.

Technical Proficiency:

• Proven experience designing, developing, and maintaining

  end-to-end data solutions

  across both

  data engineering

  and

  business intelligence

  domains.
• Strong proficiency in

  Python

  for data processing, automation, and integration.
• Hands-on experience with

  Azure Data Factory (ADF)

  ,

  Databricks

  , and

  Microsoft Fabric

  for building and orchestrating ETL/ELT pipelines.
• Solid understanding of

  data warehousing

  and

  data modeling

  principles (e.g., star/snowflake schemas, dimensional modeling).
• Proficiency in

  SQL

  and experience with

  MS SQL Server, Snowflake, PostgreSQL,

  and

  Oracle / PL-SQL

  .
• Exposure to

  NoSQL

  databases such as

  MongoDB

  and big data ecosystems (e.g.,

  Spark, Delta Lake, Azure Data Lake, Hadoop

  , or similar distributed data technologies).
• Familiarity with data integration tools and API-based data ingestion is a plus.

Business Intelligence & Visualization:

• Advanced expertise in

  Power BI

  , including

  Power Query (M language)

  ,

  DAX

  , and

  data model design

  .
• Ability to create interactive, visually compelling, and performance-optimized dashboards for business stakeholders.
• Understanding

  data storytelling

  ,

  KPI design

  , and

  user experience principles

  in dashboarding.

Performance & Optimization:

• Skilled in query tuning, data pipeline optimization, and efficient model design for large datasets.
• Experience troubleshooting performance issues across both backend and BI layers.

CI/CD:

• Experience implementing

  CI/CD pipelines

  for data workflows and BI assets using

  Azure DevOps

  ,

  Git

  , or similar tools.
• Familiarity with

  source control management

  for Power BI datasets, notebooks, and data pipeline code.
• Ability to manage deployment workflows in

  Microsoft Fabric

  .
• Understanding

  branching strategies

  ,

  code review processes

  for data and analytics projects.
• Commitment to maintaining version-controlled, auditable, and reusable analytics solutions across the data stack.

Data Science (Nice to Have):

• Experience with data science and statistical analysis, including exposure to machine learning models, predictive analytics, or forecasting techniques. (Nice to
• Familiarity with R or Python libraries such as scikit-learn, pandas, or TensorFlow for data exploration and model development

Collaboration & Communication:

• Proven ability to work cross-functionally with business and technical teams to translate requirements into scalable data solutions.
• Strong documentation, communication, and stakeholder management skills.
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